-
Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014)
0.39
0.3881072 = product of:
0.7762144 = sum of:
0.10931131 = product of:
0.32793394 = sum of:
0.32793394 = weight(_text_:3a in 1826) [ClassicSimilarity], result of:
0.32793394 = score(doc=1826,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.93669677 = fieldWeight in 1826, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.078125 = fieldNorm(doc=1826)
0.33333334 = coord(1/3)
0.32793394 = weight(_text_:2f in 1826) [ClassicSimilarity], result of:
0.32793394 = score(doc=1826,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.93669677 = fieldWeight in 1826, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.078125 = fieldNorm(doc=1826)
0.32793394 = weight(_text_:2f in 1826) [ClassicSimilarity], result of:
0.32793394 = score(doc=1826,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.93669677 = fieldWeight in 1826, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.078125 = fieldNorm(doc=1826)
0.0110352645 = product of:
0.022070529 = sum of:
0.022070529 = weight(_text_:on in 1826) [ClassicSimilarity], result of:
0.022070529 = score(doc=1826,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.24300331 = fieldWeight in 1826, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.078125 = fieldNorm(doc=1826)
0.5 = coord(1/2)
0.5 = coord(4/8)
- Content
- Präsentation anlässlich: European Conference on Data Analysis (ECDA 2014) in Bremen, Germany, July 2nd to 4th 2014, LIS-Workshop.
- Source
- http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja
-
Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019)
0.38
0.38290185 = product of:
0.5105358 = sum of:
0.06558679 = product of:
0.19676036 = sum of:
0.19676036 = weight(_text_:3a in 400) [ClassicSimilarity], result of:
0.19676036 = score(doc=400,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.56201804 = fieldWeight in 400, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=400)
0.33333334 = coord(1/3)
0.19676036 = weight(_text_:2f in 400) [ClassicSimilarity], result of:
0.19676036 = score(doc=400,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.56201804 = fieldWeight in 400, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=400)
0.025667597 = weight(_text_:use in 400) [ClassicSimilarity], result of:
0.025667597 = score(doc=400,freq=2.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.20298971 = fieldWeight in 400, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.046875 = fieldNorm(doc=400)
0.016396983 = weight(_text_:of in 400) [ClassicSimilarity], result of:
0.016396983 = score(doc=400,freq=12.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.25392252 = fieldWeight in 400, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=400)
0.19676036 = weight(_text_:2f in 400) [ClassicSimilarity], result of:
0.19676036 = score(doc=400,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.56201804 = fieldWeight in 400, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=400)
0.009363732 = product of:
0.018727465 = sum of:
0.018727465 = weight(_text_:on in 400) [ClassicSimilarity], result of:
0.018727465 = score(doc=400,freq=4.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.20619515 = fieldWeight in 400, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.046875 = fieldNorm(doc=400)
0.5 = coord(1/2)
0.75 = coord(6/8)
- Abstract
- On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as application (e.g., face recognition), model (e.g., svm, knn), and metric (e.g., precision). In this work, we aim at building faceted concept hierarchies from scientific literature. Hierarchy construction methods heavily rely on hypernym detection, however, the faceted relations are parent-to-child links but the hypernym relation is a multi-hop, i.e., ancestor-to-descendent link with a specific facet "type-of". We use information extraction techniques to find synonyms, sibling concepts, and ancestor-descendent relations from a data science corpus. And we propose a hierarchy growth algorithm to infer the parent-child links from the three types of relationships. It resolves conflicts by maintaining the acyclic structure of a hierarchy.
- Content
- Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
- Source
- Graph-Based Methods for Natural Language Processing - proceedings of the Thirteenth Workshop (TextGraphs-13): November 4, 2019, Hong Kong : EMNLP-IJCNLP 2019. Ed.: Dmitry Ustalov
-
Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012)
0.35
0.34568116 = product of:
0.4609082 = sum of:
0.025048172 = weight(_text_:retrieval in 563) [ClassicSimilarity], result of:
0.025048172 = score(doc=563,freq=2.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.20052543 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.19676036 = weight(_text_:2f in 563) [ClassicSimilarity], result of:
0.19676036 = score(doc=563,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.56201804 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.018933605 = weight(_text_:of in 563) [ClassicSimilarity], result of:
0.018933605 = score(doc=563,freq=16.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.2932045 = fieldWeight in 563, product of:
4.0 = tf(freq=16.0), with freq of:
16.0 = termFreq=16.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.19676036 = weight(_text_:2f in 563) [ClassicSimilarity], result of:
0.19676036 = score(doc=563,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.56201804 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.006621159 = product of:
0.013242318 = sum of:
0.013242318 = weight(_text_:on in 563) [ClassicSimilarity], result of:
0.013242318 = score(doc=563,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.14580199 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.5 = coord(1/2)
0.016784549 = product of:
0.033569098 = sum of:
0.033569098 = weight(_text_:22 in 563) [ClassicSimilarity], result of:
0.033569098 = score(doc=563,freq=2.0), product of:
0.1446067 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041294612 = queryNorm
0.23214069 = fieldWeight in 563, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=563)
0.5 = coord(1/2)
0.75 = coord(6/8)
- Abstract
- In this thesis we propose three new word association measures for multi-word term extraction. We combine these association measures with LocalMaxs algorithm in our extraction model and compare the results of different multi-word term extraction methods. Our approach is language and domain independent and requires no training data. It can be applied to such tasks as text summarization, information retrieval, and document classification. We further explore the potential of using multi-word terms as an effective representation for general web-page summarization. We extract multi-word terms from human written summaries in a large collection of web-pages, and generate the summaries by aligning document words with these multi-word terms. Our system applies machine translation technology to learn the aligning process from a training set and focuses on selecting high quality multi-word terms from human written summaries to generate suitable results for web-page summarization.
- Content
- A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.
- Date
- 10. 1.2013 19:22:47
- Imprint
- Guelph, Ontario : University of Guelph
-
Farazi, M.: Faceted lightweight ontologies : a formalization and some experiments (2010)
0.32
0.3227769 = product of:
0.43036923 = sum of:
0.054655656 = product of:
0.16396697 = sum of:
0.16396697 = weight(_text_:3a in 4997) [ClassicSimilarity], result of:
0.16396697 = score(doc=4997,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.46834838 = fieldWeight in 4997, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.0390625 = fieldNorm(doc=4997)
0.33333334 = coord(1/3)
0.16396697 = weight(_text_:2f in 4997) [ClassicSimilarity], result of:
0.16396697 = score(doc=4997,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.46834838 = fieldWeight in 4997, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.0390625 = fieldNorm(doc=4997)
0.021389665 = weight(_text_:use in 4997) [ClassicSimilarity], result of:
0.021389665 = score(doc=4997,freq=2.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.1691581 = fieldWeight in 4997, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=4997)
0.02087234 = weight(_text_:of in 4997) [ClassicSimilarity], result of:
0.02087234 = score(doc=4997,freq=28.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.32322758 = fieldWeight in 4997, product of:
5.2915025 = tf(freq=28.0), with freq of:
28.0 = termFreq=28.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=4997)
0.16396697 = weight(_text_:2f in 4997) [ClassicSimilarity], result of:
0.16396697 = score(doc=4997,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.46834838 = fieldWeight in 4997, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.0390625 = fieldNorm(doc=4997)
0.0055176322 = product of:
0.0110352645 = sum of:
0.0110352645 = weight(_text_:on in 4997) [ClassicSimilarity], result of:
0.0110352645 = score(doc=4997,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.121501654 = fieldWeight in 4997, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=4997)
0.5 = coord(1/2)
0.75 = coord(6/8)
- Abstract
- While classifications are heavily used to categorize web content, the evolution of the web foresees a more formal structure - ontology - which can serve this purpose. Ontologies are core artifacts of the Semantic Web which enable machines to use inference rules to conduct automated reasoning on data. Lightweight ontologies bridge the gap between classifications and ontologies. A lightweight ontology (LO) is an ontology representing a backbone taxonomy where the concept of the child node is more specific than the concept of the parent node. Formal lightweight ontologies can be generated from their informal ones. The key applications of formal lightweight ontologies are document classification, semantic search, and data integration. However, these applications suffer from the following problems: the disambiguation accuracy of the state of the art NLP tools used in generating formal lightweight ontologies from their informal ones; the lack of background knowledge needed for the formal lightweight ontologies; and the limitation of ontology reuse. In this dissertation, we propose a novel solution to these problems in formal lightweight ontologies; namely, faceted lightweight ontology (FLO). FLO is a lightweight ontology in which terms, present in each node label, and their concepts, are available in the background knowledge (BK), which is organized as a set of facets. A facet can be defined as a distinctive property of the groups of concepts that can help in differentiating one group from another. Background knowledge can be defined as a subset of a knowledge base, such as WordNet, and often represents a specific domain.
- Content
- PhD Dissertation at International Doctorate School in Information and Communication Technology. Vgl.: https%3A%2F%2Fcore.ac.uk%2Fdownload%2Fpdf%2F150083013.pdf&usg=AOvVaw2n-qisNagpyT0lli_6QbAQ.
- Imprint
- Trento : University / Department of information engineering and computer science
-
Xiong, C.: Knowledge based text representations for information retrieval (2016)
0.29
0.29088807 = product of:
0.46542093 = sum of:
0.04372453 = product of:
0.13117358 = sum of:
0.13117358 = weight(_text_:3a in 5820) [ClassicSimilarity], result of:
0.13117358 = score(doc=5820,freq=2.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.3746787 = fieldWeight in 5820, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03125 = fieldNorm(doc=5820)
0.33333334 = coord(1/3)
0.033397563 = weight(_text_:retrieval in 5820) [ClassicSimilarity], result of:
0.033397563 = score(doc=5820,freq=8.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.26736724 = fieldWeight in 5820, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03125 = fieldNorm(doc=5820)
0.18550745 = weight(_text_:2f in 5820) [ClassicSimilarity], result of:
0.18550745 = score(doc=5820,freq=4.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.5298757 = fieldWeight in 5820, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03125 = fieldNorm(doc=5820)
0.01728394 = weight(_text_:of in 5820) [ClassicSimilarity], result of:
0.01728394 = score(doc=5820,freq=30.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.26765788 = fieldWeight in 5820, product of:
5.477226 = tf(freq=30.0), with freq of:
30.0 = termFreq=30.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.03125 = fieldNorm(doc=5820)
0.18550745 = weight(_text_:2f in 5820) [ClassicSimilarity], result of:
0.18550745 = score(doc=5820,freq=4.0), product of:
0.35009617 = queryWeight, product of:
8.478011 = idf(docFreq=24, maxDocs=44218)
0.041294612 = queryNorm
0.5298757 = fieldWeight in 5820, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
8.478011 = idf(docFreq=24, maxDocs=44218)
0.03125 = fieldNorm(doc=5820)
0.625 = coord(5/8)
- Abstract
- The successes of information retrieval (IR) in recent decades were built upon bag-of-words representations. Effective as it is, bag-of-words is only a shallow text understanding; there is a limited amount of information for document ranking in the word space. This dissertation goes beyond words and builds knowledge based text representations, which embed the external and carefully curated information from knowledge bases, and provide richer and structured evidence for more advanced information retrieval systems. This thesis research first builds query representations with entities associated with the query. Entities' descriptions are used by query expansion techniques that enrich the query with explanation terms. Then we present a general framework that represents a query with entities that appear in the query, are retrieved by the query, or frequently show up in the top retrieved documents. A latent space model is developed to jointly learn the connections from query to entities and the ranking of documents, modeling the external evidence from knowledge bases and internal ranking features cooperatively. To further improve the quality of relevant entities, a defining factor of our query representations, we introduce learning to rank to entity search and retrieve better entities from knowledge bases. In the document representation part, this thesis research also moves one step forward with a bag-of-entities model, in which documents are represented by their automatic entity annotations, and the ranking is performed in the entity space.
This proposal includes plans to improve the quality of relevant entities with a co-learning framework that learns from both entity labels and document labels. We also plan to develop a hybrid ranking system that combines word based and entity based representations together with their uncertainties considered. At last, we plan to enrich the text representations with connections between entities. We propose several ways to infer entity graph representations for texts, and to rank documents using their structure representations. This dissertation overcomes the limitation of word based representations with external and carefully curated information from knowledge bases. We believe this thesis research is a solid start towards the new generation of intelligent, semantic, and structured information retrieval.
- Content
- Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
- Imprint
- Pittsburgh, PA : Carnegie Mellon University, School of Computer Science, Language Technologies Institute
-
Inskip, C.: Music information retrieval research (2011)
0.08
0.079513825 = product of:
0.12722212 = sum of:
0.04174695 = weight(_text_:retrieval in 13) [ClassicSimilarity], result of:
0.04174695 = score(doc=13,freq=8.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.33420905 = fieldWeight in 13, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=13)
0.021389665 = weight(_text_:use in 13) [ClassicSimilarity], result of:
0.021389665 = score(doc=13,freq=2.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.1691581 = fieldWeight in 13, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=13)
0.023000197 = weight(_text_:of in 13) [ClassicSimilarity], result of:
0.023000197 = score(doc=13,freq=34.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.35617945 = fieldWeight in 13, product of:
5.8309517 = tf(freq=34.0), with freq of:
34.0 = termFreq=34.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=13)
0.00955682 = product of:
0.01911364 = sum of:
0.01911364 = weight(_text_:on in 13) [ClassicSimilarity], result of:
0.01911364 = score(doc=13,freq=6.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.21044704 = fieldWeight in 13, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=13)
0.5 = coord(1/2)
0.031528484 = product of:
0.06305697 = sum of:
0.06305697 = weight(_text_:computers in 13) [ClassicSimilarity], result of:
0.06305697 = score(doc=13,freq=2.0), product of:
0.21710795 = queryWeight, product of:
5.257537 = idf(docFreq=625, maxDocs=44218)
0.041294612 = queryNorm
0.29044062 = fieldWeight in 13, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.257537 = idf(docFreq=625, maxDocs=44218)
0.0390625 = fieldNorm(doc=13)
0.5 = coord(1/2)
0.625 = coord(5/8)
- Abstract
- There is a long history of music librarianship in the domain of printed Western classical music. Special schemes have been developed to aid in the organization and retrieval of musical works, and existing schemes have been widely used to include these types of documents in larger physical library collections. However, the advent of digital consumer technology in the form of MP3 players and mobile phones, combined with the enormous impact of the internet and the digitization and ease of compression of audio files, has brought new formats and types of user interaction to the fore. This has led to an explosion in music information-retrieval research, concentrating on how most beneficially to use computers to organize, search and retrieve music information and recordings from large digital collections. Many of us today carry around music collections of thousands of digitized music recordings and access all manner of types of music on the web, but still are unsure what to listen to next: the enormous size of these collections and the instant accessibility of 8 million Western pop, classical, jazz and folk songs can cause confusion and trepidation. Where the classical music researcher would previously have consulted academic texts and visited a specialist music library, or the post-rock listener would have read the New Musical Express and visited the Rough Trade shop for advice on what was coming up, now we access music through hand-held devices and laptops. The issue is no longer 'I hope I can find that Velvet Underground live album somewhere this year, I wonder what it sounds like', but 'Which Velvet Underground live track shall I read about/ download/ stream now?
- Source
- Innovations in information retrieval: perspectives for theory and practice. Eds.: A. Foster, u. P. Rafferty
-
Ruhl, M.: Do we need metadata? : an on-line survey in German archives (2012)
0.07
0.073057234 = product of:
0.19481929 = sum of:
0.025667597 = weight(_text_:use in 471) [ClassicSimilarity], result of:
0.025667597 = score(doc=471,freq=2.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.20298971 = fieldWeight in 471, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.046875 = fieldNorm(doc=471)
0.014968331 = weight(_text_:of in 471) [ClassicSimilarity], result of:
0.014968331 = score(doc=471,freq=10.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.23179851 = fieldWeight in 471, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=471)
0.15418336 = sum of:
0.032436922 = weight(_text_:on in 471) [ClassicSimilarity], result of:
0.032436922 = score(doc=471,freq=12.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.35714048 = fieldWeight in 471, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.046875 = fieldNorm(doc=471)
0.12174644 = weight(_text_:line in 471) [ClassicSimilarity], result of:
0.12174644 = score(doc=471,freq=4.0), product of:
0.23157367 = queryWeight, product of:
5.6078424 = idf(docFreq=440, maxDocs=44218)
0.041294612 = queryNorm
0.52573526 = fieldWeight in 471, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
5.6078424 = idf(docFreq=440, maxDocs=44218)
0.046875 = fieldNorm(doc=471)
0.375 = coord(3/8)
- Abstract
- The paper summarizes the results of an on-line survey which was executed 2010 in german archives of all branches. The survey focused on metadata and used metadata standards for the annotation of audiovisual media like pictures, audio and video files (analog and digital). The findings motivate the question whether archives are able to collaborate in projects like europeana if they do not use accepted standards for their orientation. Archives need more resources and archival staff need more training to execute more complex tasks in an digital and semantic surrounding.
- Source
- Proceedings of the 2nd International Workshop on Semantic Digital Archives held in conjunction with the 16th Int. Conference on Theory and Practice of Digital Libraries (TPDL) on September 27, 2012 in Paphos, Cyprus [http://ceur-ws.org/Vol-912/proceedings.pdf]. Eds.: A. Mitschik et al
-
Fluhr, C.: Crosslingual access to photo databases (2012)
0.07
0.069903165 = product of:
0.11184507 = sum of:
0.025048172 = weight(_text_:retrieval in 93) [ClassicSimilarity], result of:
0.025048172 = score(doc=93,freq=2.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.20052543 = fieldWeight in 93, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=93)
0.044457585 = weight(_text_:use in 93) [ClassicSimilarity], result of:
0.044457585 = score(doc=93,freq=6.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.35158852 = fieldWeight in 93, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.046875 = fieldNorm(doc=93)
0.018933605 = weight(_text_:of in 93) [ClassicSimilarity], result of:
0.018933605 = score(doc=93,freq=16.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.2932045 = fieldWeight in 93, product of:
4.0 = tf(freq=16.0), with freq of:
16.0 = termFreq=16.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=93)
0.006621159 = product of:
0.013242318 = sum of:
0.013242318 = weight(_text_:on in 93) [ClassicSimilarity], result of:
0.013242318 = score(doc=93,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.14580199 = fieldWeight in 93, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.046875 = fieldNorm(doc=93)
0.5 = coord(1/2)
0.016784549 = product of:
0.033569098 = sum of:
0.033569098 = weight(_text_:22 in 93) [ClassicSimilarity], result of:
0.033569098 = score(doc=93,freq=2.0), product of:
0.1446067 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041294612 = queryNorm
0.23214069 = fieldWeight in 93, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.046875 = fieldNorm(doc=93)
0.5 = coord(1/2)
0.625 = coord(5/8)
- Abstract
- This paper is about search of photos in photo databases of agencies which sell photos over the Internet. The problem is far from the behavior of photo databases managed by librarians and also far from the corpora generally used for research purposes. The descriptions use mainly single words and it is well known that it is not the best way to have a good search. This increases the problem of semantic ambiguity. This problem of semantic ambiguity is crucial for cross-language querying. On the other hand, users are not aware of documentation techniques and use generally very simple queries but want to get precise answers. This paper gives the experience gained in a 3 year use (2006-2008) of a cross-language access to several of the main international commercial photo databases. The languages used were French, English, and German.
- Date
- 17. 4.2012 14:25:22
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Guidi, F.; Sacerdoti Coen, C.: ¬A survey on retrieval of mathematical knowledge (2015)
0.07
0.069100894 = product of:
0.13820179 = sum of:
0.07230785 = weight(_text_:retrieval in 5865) [ClassicSimilarity], result of:
0.07230785 = score(doc=5865,freq=6.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.5788671 = fieldWeight in 5865, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.078125 = fieldNorm(doc=5865)
0.02231347 = weight(_text_:of in 5865) [ClassicSimilarity], result of:
0.02231347 = score(doc=5865,freq=8.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.34554482 = fieldWeight in 5865, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.078125 = fieldNorm(doc=5865)
0.015606222 = product of:
0.031212443 = sum of:
0.031212443 = weight(_text_:on in 5865) [ClassicSimilarity], result of:
0.031212443 = score(doc=5865,freq=4.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.3436586 = fieldWeight in 5865, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.078125 = fieldNorm(doc=5865)
0.5 = coord(1/2)
0.02797425 = product of:
0.0559485 = sum of:
0.0559485 = weight(_text_:22 in 5865) [ClassicSimilarity], result of:
0.0559485 = score(doc=5865,freq=2.0), product of:
0.1446067 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041294612 = queryNorm
0.38690117 = fieldWeight in 5865, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.078125 = fieldNorm(doc=5865)
0.5 = coord(1/2)
0.5 = coord(4/8)
- Abstract
- We present a short survey of the literature on indexing and retrieval of mathematical knowledge, with pointers to 72 papers and tentative taxonomies of both retrieval problems and recurring techniques.
- Date
- 22. 2.2017 12:51:57
-
Hjoerland, B.: Classical databases and knowledge organisation : a case for Boolean retrieval and human decision-making during search (2014)
0.07
0.06797431 = product of:
0.10875889 = sum of:
0.051129367 = weight(_text_:retrieval in 1398) [ClassicSimilarity], result of:
0.051129367 = score(doc=1398,freq=12.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.40932083 = fieldWeight in 1398, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=1398)
0.021389665 = weight(_text_:use in 1398) [ClassicSimilarity], result of:
0.021389665 = score(doc=1398,freq=2.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.1691581 = fieldWeight in 1398, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=1398)
0.0167351 = weight(_text_:of in 1398) [ClassicSimilarity], result of:
0.0167351 = score(doc=1398,freq=18.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.25915858 = fieldWeight in 1398, product of:
4.2426405 = tf(freq=18.0), with freq of:
18.0 = termFreq=18.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=1398)
0.0055176322 = product of:
0.0110352645 = sum of:
0.0110352645 = weight(_text_:on in 1398) [ClassicSimilarity], result of:
0.0110352645 = score(doc=1398,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.121501654 = fieldWeight in 1398, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=1398)
0.5 = coord(1/2)
0.013987125 = product of:
0.02797425 = sum of:
0.02797425 = weight(_text_:22 in 1398) [ClassicSimilarity], result of:
0.02797425 = score(doc=1398,freq=2.0), product of:
0.1446067 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041294612 = queryNorm
0.19345059 = fieldWeight in 1398, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=1398)
0.5 = coord(1/2)
0.625 = coord(5/8)
- Abstract
- This paper considers classical bibliographic databases based on the Boolean retrieval model (for example MEDLINE and PsycInfo). This model is challenged by modern search engines and information retrieval (IR) researchers, who often consider Boolean retrieval as a less efficient approach. This speech examines this claim and argues for the continued value of Boolean systems, which implies two further issues: (1) the important role of human expertise in searching (expert searchers and "information literacy") and (2) the role of knowledge organization (KO) in the design and use of classical databases, including controlled vocabularies and human indexing. An underlying issue is the kind of retrieval system for which one should aim. It is suggested that Julian Warner's (2010) differentiation between the computer science traditions, aiming at automatically transforming queries into (ranked) sets of relevant documents, and an older library-orientated tradition aiming at increasing the "selection power" of users seems important. The Boolean retrieval model is important in order to provide users with the power to make informed searches and have full control over what is found and what is not found. These issues may also have important implications for the maintenance of information science and KO as research fields as well as for the information profession as a profession in its own right.
- Source
- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
-
Bhatia, S.; Biyani, P.; Mitra, P.: Identifying the role of individual user messages in an online discussion and its use in thread retrieval (2016)
0.07
0.06719859 = product of:
0.10751775 = sum of:
0.036153924 = weight(_text_:retrieval in 2650) [ClassicSimilarity], result of:
0.036153924 = score(doc=2650,freq=6.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.28943354 = fieldWeight in 2650, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=2650)
0.030249555 = weight(_text_:use in 2650) [ClassicSimilarity], result of:
0.030249555 = score(doc=2650,freq=4.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.23922569 = fieldWeight in 2650, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=2650)
0.019324033 = weight(_text_:of in 2650) [ClassicSimilarity], result of:
0.019324033 = score(doc=2650,freq=24.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.2992506 = fieldWeight in 2650, product of:
4.8989797 = tf(freq=24.0), with freq of:
24.0 = termFreq=24.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=2650)
0.007803111 = product of:
0.015606222 = sum of:
0.015606222 = weight(_text_:on in 2650) [ClassicSimilarity], result of:
0.015606222 = score(doc=2650,freq=4.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.1718293 = fieldWeight in 2650, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=2650)
0.5 = coord(1/2)
0.013987125 = product of:
0.02797425 = sum of:
0.02797425 = weight(_text_:22 in 2650) [ClassicSimilarity], result of:
0.02797425 = score(doc=2650,freq=2.0), product of:
0.1446067 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041294612 = queryNorm
0.19345059 = fieldWeight in 2650, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=2650)
0.5 = coord(1/2)
0.625 = coord(5/8)
- Abstract
- Online discussion forums have become a popular medium for users to discuss with and seek information from other users having similar interests. A typical discussion thread consists of a sequence of posts posted by multiple users. Each post in a thread serves a different purpose providing different types of information and, thus, may not be equally useful for all applications. Identifying the purpose and nature of each post in a discussion thread is thus an interesting research problem as it can help in improving information extraction and intelligent assistance techniques. We study the problem of classifying a given post as per its purpose in the discussion thread and employ features based on the post's content, structure of the thread, behavior of the participating users, and sentiment analysis of the post's content. We evaluate our approach on two forum data sets belonging to different genres and achieve strong classification performance. We also analyze the relative importance of different features used for the post classification task. Next, as a use case, we describe how the post class information can help in thread retrieval by incorporating this information in a state-of-the-art thread retrieval model.
- Date
- 22. 1.2016 11:50:46
- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.2, S.276-288
-
Bergman, O.; Whittaker, S.; Falk, N.: Shared files : the retrieval perspective (2014)
0.07
0.06605497 = product of:
0.105687946 = sum of:
0.051129367 = weight(_text_:retrieval in 1495) [ClassicSimilarity], result of:
0.051129367 = score(doc=1495,freq=12.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.40932083 = fieldWeight in 1495, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=1495)
0.021389665 = weight(_text_:use in 1495) [ClassicSimilarity], result of:
0.021389665 = score(doc=1495,freq=2.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.1691581 = fieldWeight in 1495, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=1495)
0.013664153 = weight(_text_:of in 1495) [ClassicSimilarity], result of:
0.013664153 = score(doc=1495,freq=12.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.21160212 = fieldWeight in 1495, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=1495)
0.0055176322 = product of:
0.0110352645 = sum of:
0.0110352645 = weight(_text_:on in 1495) [ClassicSimilarity], result of:
0.0110352645 = score(doc=1495,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.121501654 = fieldWeight in 1495, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=1495)
0.5 = coord(1/2)
0.013987125 = product of:
0.02797425 = sum of:
0.02797425 = weight(_text_:22 in 1495) [ClassicSimilarity], result of:
0.02797425 = score(doc=1495,freq=2.0), product of:
0.1446067 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041294612 = queryNorm
0.19345059 = fieldWeight in 1495, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=1495)
0.5 = coord(1/2)
0.625 = coord(5/8)
- Abstract
- People who are collaborating can share files in two main ways: performing Group Information Management (GIM) using a common repository or performing Personal Information Management (PIM) by distributing files as e-mail attachments and storing them in personal repositories. There is a trend toward using common repositories with many organizations encouraging workers to use GIM to avoid duplication of files and management. So far, PIM and GIM have been studied by different research communities, so their effectiveness for file retrieval has not yet been systematically compared. We compared PIM and GIM in a large-scale elicited personal information retrieval study. We asked 275 users to retrieve 860 of their own shared files, testing the effect of sharing method on success and efficiency of retrieval. Participants preferred PIM over GIM. More important, PIM retrieval was more successful: Participants using GIM failed to find 22% of their files compared with 13% failures using PIM. This may be because active organization aids retrieval: When using personally created folders, the failure percentage was 65% lower than when using default folders (e.g., My Documents), and more than 5 times lower than when using folders created by others for GIM. Theoretical reasons for this are discussed.
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.10, S.1949-1963
-
Zhou, D.; Lawless, S.; Wu, X.; Zhao, W.; Liu, J.: ¬A study of user profile representation for personalized cross-language information retrieval (2016)
0.06
0.06471715 = product of:
0.10354745 = sum of:
0.036153924 = weight(_text_:retrieval in 3167) [ClassicSimilarity], result of:
0.036153924 = score(doc=3167,freq=6.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.28943354 = fieldWeight in 3167, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=3167)
0.021389665 = weight(_text_:use in 3167) [ClassicSimilarity], result of:
0.021389665 = score(doc=3167,freq=2.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.1691581 = fieldWeight in 3167, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=3167)
0.01850135 = weight(_text_:of in 3167) [ClassicSimilarity], result of:
0.01850135 = score(doc=3167,freq=22.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.28651062 = fieldWeight in 3167, product of:
4.690416 = tf(freq=22.0), with freq of:
22.0 = termFreq=22.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=3167)
0.013515383 = product of:
0.027030766 = sum of:
0.027030766 = weight(_text_:on in 3167) [ClassicSimilarity], result of:
0.027030766 = score(doc=3167,freq=12.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.29761705 = fieldWeight in 3167, product of:
3.4641016 = tf(freq=12.0), with freq of:
12.0 = termFreq=12.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=3167)
0.5 = coord(1/2)
0.013987125 = product of:
0.02797425 = sum of:
0.02797425 = weight(_text_:22 in 3167) [ClassicSimilarity], result of:
0.02797425 = score(doc=3167,freq=2.0), product of:
0.1446067 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041294612 = queryNorm
0.19345059 = fieldWeight in 3167, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=3167)
0.5 = coord(1/2)
0.625 = coord(5/8)
- Abstract
- Purpose - With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion. Design/methodology/approach - The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods. Findings - Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level. Originality/value - Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted.
- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 68(2016) no.4, S.448-477
-
Giri, K.; Gokhale, P.: Developing a banking service ontology using Protégé, an open source software (2015)
0.06
0.0641703 = product of:
0.10267249 = sum of:
0.020873476 = weight(_text_:retrieval in 2793) [ClassicSimilarity], result of:
0.020873476 = score(doc=2793,freq=2.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.16710453 = fieldWeight in 2793, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=2793)
0.021389665 = weight(_text_:use in 2793) [ClassicSimilarity], result of:
0.021389665 = score(doc=2793,freq=2.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.1691581 = fieldWeight in 2793, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=2793)
0.019324033 = weight(_text_:of in 2793) [ClassicSimilarity], result of:
0.019324033 = score(doc=2793,freq=24.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.2992506 = fieldWeight in 2793, product of:
4.8989797 = tf(freq=24.0), with freq of:
24.0 = termFreq=24.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=2793)
0.00955682 = product of:
0.01911364 = sum of:
0.01911364 = weight(_text_:on in 2793) [ClassicSimilarity], result of:
0.01911364 = score(doc=2793,freq=6.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.21044704 = fieldWeight in 2793, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=2793)
0.5 = coord(1/2)
0.031528484 = product of:
0.06305697 = sum of:
0.06305697 = weight(_text_:computers in 2793) [ClassicSimilarity], result of:
0.06305697 = score(doc=2793,freq=2.0), product of:
0.21710795 = queryWeight, product of:
5.257537 = idf(docFreq=625, maxDocs=44218)
0.041294612 = queryNorm
0.29044062 = fieldWeight in 2793, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.257537 = idf(docFreq=625, maxDocs=44218)
0.0390625 = fieldNorm(doc=2793)
0.5 = coord(1/2)
0.625 = coord(5/8)
- Abstract
- Computers have transformed from single isolated devices to entry points into a worldwide network of information exchange. Consequently, support in the exchange of data, information, and knowledge is becoming the key issue in computer technology today. The increasing volume of data available on the Web makes information retrieval a tedious and difficult task. Researchers are now exploring the possibility of creating a semantic web, in which meaning is made explicit, allowing machines to process and integrate web resources intelligently. The vision of the semantic web introduces the next generation of the Web by establishing a layer of machine-understandable data. The success of the semantic web depends on the easy creation, integration and use of semantic data, which will depend on web ontology. The faceted approach towards analyzing and representing knowledge given by S R Ranganathan would be useful in this regard. Ontology development in different fields is one such area where this approach given by Ranganathan could be applied. This paper presents a case of developing ontology for the field of banking.
- Source
- Annals of library and information studies. 62(2015) no.4, S.281-285
-
Padmavathi, T.; Krishnamurthy, M.: Ontological representation of knowledge for developing information services in food science and technology (2012)
0.06
0.063973054 = product of:
0.17059481 = sum of:
0.050096344 = weight(_text_:retrieval in 839) [ClassicSimilarity], result of:
0.050096344 = score(doc=839,freq=8.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.40105087 = fieldWeight in 839, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=839)
0.021168415 = weight(_text_:of in 839) [ClassicSimilarity], result of:
0.021168415 = score(doc=839,freq=20.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.32781258 = fieldWeight in 839, product of:
4.472136 = tf(freq=20.0), with freq of:
20.0 = termFreq=20.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.046875 = fieldNorm(doc=839)
0.099330045 = sum of:
0.013242318 = weight(_text_:on in 839) [ClassicSimilarity], result of:
0.013242318 = score(doc=839,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.14580199 = fieldWeight in 839, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.046875 = fieldNorm(doc=839)
0.086087726 = weight(_text_:line in 839) [ClassicSimilarity], result of:
0.086087726 = score(doc=839,freq=2.0), product of:
0.23157367 = queryWeight, product of:
5.6078424 = idf(docFreq=440, maxDocs=44218)
0.041294612 = queryNorm
0.37175092 = fieldWeight in 839, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.6078424 = idf(docFreq=440, maxDocs=44218)
0.046875 = fieldNorm(doc=839)
0.375 = coord(3/8)
- Abstract
- Knowledge explosion in various fields during recent years has resulted in the creation of vast amounts of on-line scientific literature. Food Science &Technology (FST) is also an important subject domain where rapid developments are taking place due to diverse research and development activities. As a result, information storage and retrieval has become very complex and current information retrieval systems (IRs) are being challenged in terms of both adequate precision and response time. To overcome these limitations as well as to provide naturallanguage based effective retrieval, a suitable knowledge engineering framework needs to be applied to represent, share and discover information. Semantic web technologies provide mechanisms for creating knowledge bases, ontologies and rules for handling data that promise to improve the quality of information retrieval. Ontologies are the backbone of such knowledge systems. This paper presents a framework for semantic representation of a large repository of content in the domain of FST.
- Source
- Categories, contexts and relations in knowledge organization: Proceedings of the Twelfth International ISKO Conference 6-9 August 2012, Mysore, India. Eds.: Neelameghan, A. u. K.S. Raghavan
-
Yuan, X. (J.); Belkin, N.J.: Applying an information-seeking dialogue model in an interactive information retrieval system (2014)
0.06
0.063656434 = product of:
0.1018503 = sum of:
0.029519552 = weight(_text_:retrieval in 4544) [ClassicSimilarity], result of:
0.029519552 = score(doc=4544,freq=4.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.23632148 = fieldWeight in 4544, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=4544)
0.037047986 = weight(_text_:use in 4544) [ClassicSimilarity], result of:
0.037047986 = score(doc=4544,freq=6.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.29299045 = fieldWeight in 4544, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=4544)
0.015778005 = weight(_text_:of in 4544) [ClassicSimilarity], result of:
0.015778005 = score(doc=4544,freq=16.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.24433708 = fieldWeight in 4544, product of:
4.0 = tf(freq=16.0), with freq of:
16.0 = termFreq=16.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=4544)
0.0055176322 = product of:
0.0110352645 = sum of:
0.0110352645 = weight(_text_:on in 4544) [ClassicSimilarity], result of:
0.0110352645 = score(doc=4544,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.121501654 = fieldWeight in 4544, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=4544)
0.5 = coord(1/2)
0.013987125 = product of:
0.02797425 = sum of:
0.02797425 = weight(_text_:22 in 4544) [ClassicSimilarity], result of:
0.02797425 = score(doc=4544,freq=2.0), product of:
0.1446067 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041294612 = queryNorm
0.19345059 = fieldWeight in 4544, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0390625 = fieldNorm(doc=4544)
0.5 = coord(1/2)
0.625 = coord(5/8)
- Abstract
- Purpose - People often engage in different information-seeking strategies (ISSs) within a single information-seeking episode. A critical concern for the design of information retrieval (IR) systems is how to provide support for these different behaviors in a manner which searchers can easily understand, navigate and use, as they move from one ISS to another. The purpose of this paper is to describe a dialogue structure that was implemented in an experimental IR system, in order to address this concern. Design/methodology/approach - The authors conducted a user-centered experiment to evaluate the IR systems. Participants were asked to search for information on two different task types, with four different topics per task, in both the experimental system and a baseline system emulating state-of-the-art IR systems. The authors report here the results related explicitly to the use of the experimental system's dialogue structure. Findings - For one of the task types, most participants followed the search steps as predicted in the dialogue structures, and those who did so completed the task in fewer moves. For the other task type, predicted order of moves was often not followed, but participants again used fewer moves when following the predicted order. Results demonstrate that the dialogue structures the authors designed indeed support effective human information behavior patterns in a variety of ways, and that searchers can effectively use a system which changes to support different ISSs. Originality/value - This study shows that it is both possible and beneficial, to design an IR system which can support multiple ISSs, and that such a system can be understood and used successfully.
- Date
- 6. 4.2015 19:22:59
- Source
- Journal of documentation. 70(2014) no.5, S.829-855
-
Pinto, V.B.; Rabelo, C.R. de Oliveira; Girão, I.P.T.: SNOMED-CT as standard language for organization and representation of the information in patient records (2014)
0.06
0.06345259 = product of:
0.12690517 = sum of:
0.023615643 = weight(_text_:retrieval in 1396) [ClassicSimilarity], result of:
0.023615643 = score(doc=1396,freq=4.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.18905719 = fieldWeight in 1396, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03125 = fieldNorm(doc=1396)
0.01711173 = weight(_text_:use in 1396) [ClassicSimilarity], result of:
0.01711173 = score(doc=1396,freq=2.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.13532647 = fieldWeight in 1396, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.03125 = fieldNorm(doc=1396)
0.019957775 = weight(_text_:of in 1396) [ClassicSimilarity], result of:
0.019957775 = score(doc=1396,freq=40.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.3090647 = fieldWeight in 1396, product of:
6.3245554 = tf(freq=40.0), with freq of:
40.0 = termFreq=40.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.03125 = fieldNorm(doc=1396)
0.06622003 = sum of:
0.008828212 = weight(_text_:on in 1396) [ClassicSimilarity], result of:
0.008828212 = score(doc=1396,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.097201325 = fieldWeight in 1396, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.03125 = fieldNorm(doc=1396)
0.05739182 = weight(_text_:line in 1396) [ClassicSimilarity], result of:
0.05739182 = score(doc=1396,freq=2.0), product of:
0.23157367 = queryWeight, product of:
5.6078424 = idf(docFreq=440, maxDocs=44218)
0.041294612 = queryNorm
0.24783395 = fieldWeight in 1396, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
5.6078424 = idf(docFreq=440, maxDocs=44218)
0.03125 = fieldNorm(doc=1396)
0.5 = coord(4/8)
- Abstract
- The Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT), such as the Medical Subject Headings (MeSH) and the Health Sciences Descriptors (MeSH) is a standard for handling, organizing, representing and retrieval of information in the health context. It is structured, among other things, in 19 categories: clinical diagnosis/disease, procedures, observable entities, body structure, body, substance, biological and pharmaceutical products, sample, physical object, physical force, event, geographical or environmental location, social context, stages and scales, special concepts and qualifiers. We present research results carried out with patients' medical records in the Walter Cantidio University Hospital, at Federal University of Ceará. The line guiding this study seeks to answer the following question: what is the contribution of these categories to build a representation of the patient's medical records at the Department of Medical Records and Statistics (SAME), at the Walter Cantidio University Hospital (HUWC)? The objective of the research is to study the contribution of SNOMED-CT for the representation of information within those records. It is therefore an exploratory study supported by neofunctionalist method and content analysis, the physical structure of digitized records was analyzed at the SAME of the HUWC. Then we analyzed a corpus of two patient records with nine volumes, about 4000 pages corresponding to 777 Mb. The results and conclusions show that the hierarchical categories of SNOMED-CT may bring contributions to the representation of the charts, as it is a robust terminology based on ontology, contemplating the essence of the information recorded in these documents. Regarding the physical structure of the chart shows some similarities, and hence can contribute to information retrieval with higher added value, since it allows the use of pre and post-coordination as well as natural language, synonyms and acronyms.
- Footnote
- Papers from I Congress of ISKO Spain and Portugal / XI Congress ISKO Spain, 7-9 November 2013, University of Porto.
-
Ayadi, H.; Torjmen-Khemakhem, M.; Daoud, M.; Huang, J.X.; Jemaa, M.B.: Mining correlations between medically dependent features and image retrieval models for query classification (2017)
0.06
0.062148638 = product of:
0.124297276 = sum of:
0.055226028 = weight(_text_:retrieval in 3607) [ClassicSimilarity], result of:
0.055226028 = score(doc=3607,freq=14.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.442117 = fieldWeight in 3607, product of:
3.7416575 = tf(freq=14.0), with freq of:
14.0 = termFreq=14.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=3607)
0.04277933 = weight(_text_:use in 3607) [ClassicSimilarity], result of:
0.04277933 = score(doc=3607,freq=8.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.3383162 = fieldWeight in 3607, product of:
2.828427 = tf(freq=8.0), with freq of:
8.0 = termFreq=8.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=3607)
0.0167351 = weight(_text_:of in 3607) [ClassicSimilarity], result of:
0.0167351 = score(doc=3607,freq=18.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.25915858 = fieldWeight in 3607, product of:
4.2426405 = tf(freq=18.0), with freq of:
18.0 = termFreq=18.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=3607)
0.00955682 = product of:
0.01911364 = sum of:
0.01911364 = weight(_text_:on in 3607) [ClassicSimilarity], result of:
0.01911364 = score(doc=3607,freq=6.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.21044704 = fieldWeight in 3607, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=3607)
0.5 = coord(1/2)
0.5 = coord(4/8)
- Abstract
- The abundance of medical resources has encouraged the development of systems that allow for efficient searches of information in large medical image data sets. State-of-the-art image retrieval models are classified into three categories: content-based (visual) models, textual models, and combined models. Content-based models use visual features to answer image queries, textual image retrieval models use word matching to answer textual queries, and combined image retrieval models, use both textual and visual features to answer queries. Nevertheless, most of previous works in this field have used the same image retrieval model independently of the query type. In this article, we define a list of generic and specific medical query features and exploit them in an association rule mining technique to discover correlations between query features and image retrieval models. Based on these rules, we propose to use an associative classifier (NaiveClass) to find the best suitable retrieval model given a new textual query. We also propose a second associative classifier (SmartClass) to select the most appropriate default class for the query. Experiments are performed on Medical ImageCLEF queries from 2008 to 2012 to evaluate the impact of the proposed query features on the classification performance. The results show that combining our proposed specific and generic query features is effective in query classification.
- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1323-1334
-
Dang, E.K.F.; Luk, R.W.P.; Allan, J.: Beyond bag-of-words : bigram-enhanced context-dependent term weights (2014)
0.06
0.06140661 = product of:
0.12281322 = sum of:
0.046674512 = weight(_text_:retrieval in 1283) [ClassicSimilarity], result of:
0.046674512 = score(doc=1283,freq=10.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.37365708 = fieldWeight in 1283, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.0390625 = fieldNorm(doc=1283)
0.037047986 = weight(_text_:use in 1283) [ClassicSimilarity], result of:
0.037047986 = score(doc=1283,freq=6.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.29299045 = fieldWeight in 1283, product of:
2.4494898 = tf(freq=6.0), with freq of:
6.0 = termFreq=6.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.0390625 = fieldNorm(doc=1283)
0.02675291 = weight(_text_:of in 1283) [ClassicSimilarity], result of:
0.02675291 = score(doc=1283,freq=46.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.41429368 = fieldWeight in 1283, product of:
6.78233 = tf(freq=46.0), with freq of:
46.0 = termFreq=46.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.0390625 = fieldNorm(doc=1283)
0.012337802 = product of:
0.024675604 = sum of:
0.024675604 = weight(_text_:on in 1283) [ClassicSimilarity], result of:
0.024675604 = score(doc=1283,freq=10.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.271686 = fieldWeight in 1283, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.0390625 = fieldNorm(doc=1283)
0.5 = coord(1/2)
0.5 = coord(4/8)
- Abstract
- While term independence is a widely held assumption in most of the established information retrieval approaches, it is clearly not true and various works in the past have investigated a relaxation of the assumption. One approach is to use n-grams in document representation instead of unigrams. However, the majority of early works on n-grams obtained only modest performance improvement. On the other hand, the use of information based on supporting terms or "contexts" of queries has been found to be promising. In particular, recent studies showed that using new context-dependent term weights improved the performance of relevance feedback (RF) retrieval compared with using traditional bag-of-words BM25 term weights. Calculation of the new term weights requires an estimation of the local probability of relevance of each query term occurrence. In previous studies, the estimation of this probability was based on unigrams that occur in the neighborhood of a query term. We explore an integration of the n-gram and context approaches by computing context-dependent term weights based on a mixture of unigrams and bigrams. Extensive experiments are performed using the title queries of the Text Retrieval Conference (TREC)-6, TREC-7, TREC-8, and TREC-2005 collections, for RF with relevance judgment of either the top 10 or top 20 documents of an initial retrieval. We identify some crucial elements needed in the use of bigrams in our methods, such as proper inverse document frequency (IDF) weighting of the bigrams and noise reduction by pruning bigrams with large document frequency values. We show that enhancing context-dependent term weights with bigrams is effective in further improving retrieval performance.
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.6, S.1134-1148
-
Kiren, T.: ¬A clustering based indexing technique of modularized ontologies for information retrieval (2017)
0.06
0.06068802 = product of:
0.09710083 = sum of:
0.03733961 = weight(_text_:retrieval in 4399) [ClassicSimilarity], result of:
0.03733961 = score(doc=4399,freq=10.0), product of:
0.124912694 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.041294612 = queryNorm
0.29892567 = fieldWeight in 4399, product of:
3.1622777 = tf(freq=10.0), with freq of:
10.0 = termFreq=10.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.03125 = fieldNorm(doc=4399)
0.024199642 = weight(_text_:use in 4399) [ClassicSimilarity], result of:
0.024199642 = score(doc=4399,freq=4.0), product of:
0.12644777 = queryWeight, product of:
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.041294612 = queryNorm
0.19138055 = fieldWeight in 4399, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
3.0620887 = idf(docFreq=5623, maxDocs=44218)
0.03125 = fieldNorm(doc=4399)
0.019957775 = weight(_text_:of in 4399) [ClassicSimilarity], result of:
0.019957775 = score(doc=4399,freq=40.0), product of:
0.06457475 = queryWeight, product of:
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.041294612 = queryNorm
0.3090647 = fieldWeight in 4399, product of:
6.3245554 = tf(freq=40.0), with freq of:
40.0 = termFreq=40.0
1.5637573 = idf(docFreq=25162, maxDocs=44218)
0.03125 = fieldNorm(doc=4399)
0.004414106 = product of:
0.008828212 = sum of:
0.008828212 = weight(_text_:on in 4399) [ClassicSimilarity], result of:
0.008828212 = score(doc=4399,freq=2.0), product of:
0.090823986 = queryWeight, product of:
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.041294612 = queryNorm
0.097201325 = fieldWeight in 4399, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
2.199415 = idf(docFreq=13325, maxDocs=44218)
0.03125 = fieldNorm(doc=4399)
0.5 = coord(1/2)
0.0111897 = product of:
0.0223794 = sum of:
0.0223794 = weight(_text_:22 in 4399) [ClassicSimilarity], result of:
0.0223794 = score(doc=4399,freq=2.0), product of:
0.1446067 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.041294612 = queryNorm
0.15476047 = fieldWeight in 4399, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.03125 = fieldNorm(doc=4399)
0.5 = coord(1/2)
0.625 = coord(5/8)
- Abstract
- Indexing plays a vital role in Information Retrieval. With the availability of huge volume of information, it has become necessary to index the information in such a way to make easier for the end users to find the information they want efficiently and accurately. Keyword-based indexing uses words as indexing terms. It is not capable of capturing the implicit relation among terms or the semantics of the words in the document. To eliminate this limitation, ontology-based indexing came into existence, which allows semantic based indexing to solve complex and indirect user queries. Ontologies are used for document indexing which allows semantic based information retrieval. Existing ontologies or the ones constructed from scratch are used presently for indexing. Constructing ontologies from scratch is a labor-intensive task and requires extensive domain knowledge whereas use of an existing ontology may leave some important concepts in documents un-annotated. Using multiple ontologies can overcome the problem of missing out concepts to a great extent, but it is difficult to manage (changes in ontologies over time by their developers) multiple ontologies and ontology heterogeneity also arises due to ontologies constructed by different ontology developers. One possible solution to managing multiple ontologies and build from scratch is to use modular ontologies for indexing.
Modular ontologies are built in modular manner by combining modules from multiple relevant ontologies. Ontology heterogeneity also arises during modular ontology construction because multiple ontologies are being dealt with, during this process. Ontologies need to be aligned before using them for modular ontology construction. The existing approaches for ontology alignment compare all the concepts of each ontology to be aligned, hence not optimized in terms of time and search space utilization. A new indexing technique is proposed based on modular ontology. An efficient ontology alignment technique is proposed to solve the heterogeneity problem during the construction of modular ontology. Results are satisfactory as Precision and Recall are improved by (8%) and (10%) respectively. The value of Pearsons Correlation Coefficient for degree of similarity, time, search space requirement, precision and recall are close to 1 which shows that the results are significant. Further research can be carried out for using modular ontology based indexing technique for Multimedia Information Retrieval and Bio-Medical information retrieval.
- Content
- Submitted to the Faculty of the Computer Science and Engineering Department of the University of Engineering and Technology Lahore in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in Computer Science (2009 - 009-PhD-CS-04). Vgl.: http://prr.hec.gov.pk/jspui/bitstream/123456789/8375/1/Taybah_Kiren_Computer_Science_HSR_2017_UET_Lahore_14.12.2017.pdf.
- Date
- 20. 1.2015 18:30:22
- Imprint
- Lahore : University of Engineering and Technology / Department of Computer Science and Engineering
