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Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016)
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- Date
- 1. 2.2016 18:25:22
- Language
- e
- Source
- Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Robertson, A.M.; Willett, P.: Applications of n-grams in textual information systems (1998)
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- Abstract
- Provides an introduction to the use of n-grams in textual information systems, where an n-gram is a string of n, usually adjacent, characters, extracted from a section of continuous text. Applications that can be implemented efficiently and effectively using sets of n-grams include spelling errors detection and correction, query expansion, information retrieval with serial, inverted and signature files, dictionary look up, text compression, and language identification
- Language
- e
- Object
- n-grams
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004)
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- Date
- 16.11.2008 16:22:48
- Language
- e
- Source
- Research and advanced technology for digital libraries : 8th European conference, ECDL 2004, Bath, UK, September 12-17, 2004 : proceedings. Eds.: Heery, R. u. E. Lyon
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Stojanovic, N.: On the query refinement in the ontology-based searching for information (2005)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Bettencourt, N.; Silva, N.; Barroso, J.: Semantically enhancing recommender systems (2016)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Kozikowski, P. et al.: Support of part-whole relations in query answering (2016)
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- Date
- 1. 2.2016 18:25:22
- Language
- e
- Source
- Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Morato, J.; Llorens, J.; Genova, G.; Moreiro, J.A.: Experiments in discourse analysis impact on information classification and retrieval algorithms (2003)
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- Abstract
- Researchers in indexing and retrieval systems have been advocating the inclusion of more contextual information to improve results. The proliferation of full-text databases and advances in computer storage capacity have made it possible to carry out text analysis by means of linguistic and extra-linguistic knowledge. Since the mid 80s, research has tended to pay more attention to context, giving discourse analysis a more central role. The research presented in this paper aims to check whether discourse variables have an impact on modern information retrieval and classification algorithms. In order to evaluate this hypothesis, a functional framework for information analysis in an automated environment has been proposed, where the n-grams (filtering) and the k-means and Chen's classification algorithms have been tested against sub-collections of documents based on the following discourse variables: "Genre", "Register", "Domain terminology", and "Document structure". The results obtained with the algorithms for the different sub-collections were compared to the MeSH information structure. These demonstrate that n-grams does not appear to have a clear dependence on discourse variables, though the k-means classification algorithm does, but only on domain terminology and document structure, and finally Chen's algorithm has a clear dependence on all of the discourse variables. This information could be used to design better classification algorithms, where discourse variables should be taken into account. Other minor conclusions drawn from these results are also presented.
- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983)
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- Date
- 30. 3.2001 13:32:22
- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Li, N.; Sun, J.: Improving Chinese term association from the linguistic perspective (2017)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002)
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- Date
- 22. 2.2003 17:25:39
22. 2.2003 18:17:40
- Language
- e
- Source
- Visual Interfaces to Digital Libraries. Eds.: Börner, K. u. C. Chen
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Brandão, W.C.; Santos, R.L.T.; Ziviani, N.; Moura, E.S. de; Silva, A.S. da: Learning to expand queries using entities (2014)
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- Date
- 22. 8.2014 17:07:50
- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Gauch, S.; Wang, J.: Corpus analysis for TREC 5 query expansion (1997)
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- Language
- e
- Source
- The Fifth Text Retrieval Conference (TREC-5). Ed.: E.M. Voorhees u. D.K. Harman
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Bayer, O.; Höhfeld, S.; Josbächer, F.; Kimm, N.; Kradepohl, I.; Kwiatkowski, M.; Puschmann, C.; Sabbagh, M.; Werner, N.; Vollmer, U.: Evaluation of an ontology-based knowledge-management-system : a case study of Convera RetrievalWare 8.0 (2005)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Roy, R.S.; Agarwal, S.; Ganguly, N.; Choudhury, M.: Syntactic complexity of Web search queries through the lenses of language models, networks and users (2016)
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- Abstract
- Across the world, millions of users interact with search engines every day to satisfy their information needs. As the Web grows bigger over time, such information needs, manifested through user search queries, also become more complex. However, there has been no systematic study that quantifies the structural complexity of Web search queries. In this research, we make an attempt towards understanding and characterizing the syntactic complexity of search queries using a multi-pronged approach. We use traditional statistical language modeling techniques to quantify and compare the perplexity of queries with natural language (NL). We then use complex network analysis for a comparative analysis of the topological properties of queries issued by real Web users and those generated by statistical models. Finally, we conduct experiments to study whether search engine users are able to identify real queries, when presented along with model-generated ones. The three complementary studies show that the syntactic structure of Web queries is more complex than what n-grams can capture, but simpler than NL. Queries, thus, seem to represent an intermediate stage between syntactic and non-syntactic communication.
- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016)
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- Language
- e
- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016)
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- Language
- e
- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Ross, J.: ¬A new way of information retrieval : 3-D indexing and concept mapping (2000)
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- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Goslin, K.; Hofmann, M.: ¬A Wikipedia powered state-based approach to automatic search query enhancement (2018)
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- Abstract
- This paper describes the development and testing of a novel Automatic Search Query Enhancement (ASQE) algorithm, the Wikipedia N Sub-state Algorithm (WNSSA), which utilises Wikipedia as the sole data source for prior knowledge. This algorithm is built upon the concept of iterative states and sub-states, harnessing the power of Wikipedia's data set and link information to identify and utilise reoccurring terms to aid term selection and weighting during enhancement. This algorithm is designed to prevent query drift by making callbacks to the user's original search intent by persisting the original query between internal states with additional selected enhancement terms. The developed algorithm has shown to improve both short and long queries by providing a better understanding of the query and available data. The proposed algorithm was compared against five existing ASQE algorithms that utilise Wikipedia as the sole data source, showing an average Mean Average Precision (MAP) improvement of 0.273 over the tested existing ASQE algorithms.
- Language
- e
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996)
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- Language
- e
- Source
- Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
