-
Medien-Informationsmanagement : Archivarische, dokumentarische, betriebswirtschaftliche, rechtliche und Berufsbild-Aspekte ; [Frühjahrstagung der Fachgruppe 7 im Jahr 2000 in Weimar und Folgetagung 2001 in Köln] (2003)
0.04
0.036816616 = product of:
0.07363323 = sum of:
0.07363323 = sum of:
0.052774455 = weight(_text_:media in 1833) [ClassicSimilarity], result of:
0.052774455 = score(doc=1833,freq=4.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.21955647 = fieldWeight in 1833, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.0234375 = fieldNorm(doc=1833)
0.020858778 = weight(_text_:22 in 1833) [ClassicSimilarity], result of:
0.020858778 = score(doc=1833,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.116070345 = fieldWeight in 1833, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0234375 = fieldNorm(doc=1833)
0.5 = coord(1/2)
- Date
- 11. 5.2008 19:49:22
- LCSH
- Mass media / Archival resources / Congresses
- Subject
- Mass media / Archival resources / Congresses
-
Ebrahimi, M.; ShafieiBavani, E.; Wong, R.; Chen, F.: Twitter user geolocation by filtering of highly mentioned users (2018)
0.03
0.026387228 = product of:
0.052774455 = sum of:
0.052774455 = product of:
0.10554891 = sum of:
0.10554891 = weight(_text_:media in 4286) [ClassicSimilarity], result of:
0.10554891 = score(doc=4286,freq=4.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.43911293 = fieldWeight in 4286, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.046875 = fieldNorm(doc=4286)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Geolocated social media data provide a powerful source of information about places and regional human behavior. Because only a small amount of social media data have been geolocation-annotated, inference techniques play a substantial role to increase the volume of annotated data. Conventional research in this area has been based on the text content of posts from a given user or the social network of the user, with some recent crossovers between the text- and network-based approaches. This paper proposes a novel approach to categorize highly-mentioned users (celebrities) into Local and Global types, and consequently use Local celebrities as location indicators. A label propagation algorithm is then used over the refined social network for geolocation inference. Finally, we propose a hybrid approach by merging a text-based method as a back-off strategy into our network-based approach. Empirical experiments over three standard Twitter benchmark data sets demonstrate that our approach outperforms state-of-the-art user geolocation methods.
-
Chowdhury, G.G.: Template mining for information extraction from digital documents (1999)
0.02
0.024335241 = product of:
0.048670482 = sum of:
0.048670482 = product of:
0.097340964 = sum of:
0.097340964 = weight(_text_:22 in 4577) [ClassicSimilarity], result of:
0.097340964 = score(doc=4577,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.5416616 = fieldWeight in 4577, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.109375 = fieldNorm(doc=4577)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Date
- 2. 4.2000 18:01:22
-
Classification, automation, and new media : Proceedings of the 24th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Passau, March 15 - 17, 2000 (2002)
0.02
0.021989357 = product of:
0.043978713 = sum of:
0.043978713 = product of:
0.08795743 = sum of:
0.08795743 = weight(_text_:media in 5997) [ClassicSimilarity], result of:
0.08795743 = score(doc=5997,freq=4.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.36592746 = fieldWeight in 5997, product of:
2.0 = tf(freq=4.0), with freq of:
4.0 = termFreq=4.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.0390625 = fieldNorm(doc=5997)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Content
- Data Analysis, Statistics, and Classification.- Pattern Recognition and Automation.- Data Mining, Information Processing, and Automation.- New Media, Web Mining, and Automation.- Applications in Management Science, Finance, and Marketing.- Applications in Medicine, Biology, Archaeology, and Others.- Author Index.- Subject Index.
-
Liu, W.; Weichselbraun, A.; Scharl, A.; Chang, E.: Semi-automatic ontology extension using spreading activation (2005)
0.02
0.021768354 = product of:
0.043536708 = sum of:
0.043536708 = product of:
0.087073416 = sum of:
0.087073416 = weight(_text_:media in 3028) [ClassicSimilarity], result of:
0.087073416 = score(doc=3028,freq=2.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.3622497 = fieldWeight in 3028, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.0546875 = fieldNorm(doc=3028)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- This paper describes a system to semi-automatically extend and refine ontologies by mining textual data from the Web sites of international online media. Expanding a seed ontology creates a semantic network through co-occurrence analysis, trigger phrase analysis, and disambiguation based on the WordNet lexical dictionary. Spreading activation then processes this semantic network to find the most probable candidates for inclusion in an extended ontology. Approaches to identifying hierarchical relationships such as subsumption, head noun analysis and WordNet consultation are used to confirm and classify the found relationships. Using a seed ontology on "climate change" as an example, this paper demonstrates how spreading activation improves the result by naturally integrating the mentioned methods.
-
KDD : techniques and applications (1998)
0.02
0.020858778 = product of:
0.041717555 = sum of:
0.041717555 = product of:
0.08343511 = sum of:
0.08343511 = weight(_text_:22 in 6783) [ClassicSimilarity], result of:
0.08343511 = score(doc=6783,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.46428138 = fieldWeight in 6783, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.09375 = fieldNorm(doc=6783)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Footnote
- A special issue of selected papers from the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), held Singapore, 22-23 Feb 1997
-
Heyer, G.; Läuter, M.; Quasthoff, U.; Wolff, C.: Texttechnologische Anwendungen am Beispiel Text Mining (2000)
0.02
0.018658588 = product of:
0.037317175 = sum of:
0.037317175 = product of:
0.07463435 = sum of:
0.07463435 = weight(_text_:media in 5565) [ClassicSimilarity], result of:
0.07463435 = score(doc=5565,freq=2.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.31049973 = fieldWeight in 5565, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.046875 = fieldNorm(doc=5565)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Source
- Sprachtechnologie für eine dynamische Wirtschaft im Medienzeitalter - Language technologies for dynamic business in the age of the media - L'ingénierie linguistique au service de la dynamisation économique à l'ère du multimédia: Tagungsakten der XXVI. Jahrestagung der Internationalen Vereinigung Sprache und Wirtschaft e.V., 23.-25.11.2000, Fachhochschule Köln. Hrsg.: K.-D. Schmitz
-
Ohly, H.P.: Bibliometric mining : added value from document analysis and retrieval (2008)
0.02
0.018658588 = product of:
0.037317175 = sum of:
0.037317175 = product of:
0.07463435 = sum of:
0.07463435 = weight(_text_:media in 2386) [ClassicSimilarity], result of:
0.07463435 = score(doc=2386,freq=2.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.31049973 = fieldWeight in 2386, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.046875 = fieldNorm(doc=2386)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Source
- Kompatibilität, Medien und Ethik in der Wissensorganisation - Compatibility, Media and Ethics in Knowledge Organization: Proceedings der 10. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation Wien, 3.-5. Juli 2006 - Proceedings of the 10th Conference of the German Section of the International Society of Knowledge Organization Vienna, 3-5 July 2006. Ed.: H.P. Ohly, S. Netscher u. K. Mitgutsch
-
Bella, A. La; Fronzetti Colladon, A.; Battistoni, E.; Castellan, S.; Francucci, M.: Assessing perceived organizational leadership styles through twitter text mining (2018)
0.02
0.018658588 = product of:
0.037317175 = sum of:
0.037317175 = product of:
0.07463435 = sum of:
0.07463435 = weight(_text_:media in 2400) [ClassicSimilarity], result of:
0.07463435 = score(doc=2400,freq=2.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.31049973 = fieldWeight in 2400, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.046875 = fieldNorm(doc=2400)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- We propose a text classification tool based on support vector machines for the assessment of organizational leadership styles, as appearing to Twitter users. We collected Twitter data over 51 days, related to the first 30 Italian organizations in the 2015 ranking of Forbes Global 2000-out of which we selected the five with the most relevant volumes of tweets. We analyzed the communication of the company leaders, together with the dialogue among the stakeholders of each company, to understand the association with perceived leadership styles and dimensions. To assess leadership profiles, we referred to the 10-factor model developed by Barchiesi and La Bella in 2007. We maintain the distinctiveness of the approach we propose, as it allows a rapid assessment of the perceived leadership capabilities of an enterprise, as they emerge from its social media interactions. It can also be used to show how companies respond and manage their communication when specific events take place, and to assess their stakeholder's reactions.
-
Wongthontham, P.; Abu-Salih, B.: Ontology-based approach for semantic data extraction from social big data : state-of-the-art and research directions (2018)
0.02
0.018658588 = product of:
0.037317175 = sum of:
0.037317175 = product of:
0.07463435 = sum of:
0.07463435 = weight(_text_:media in 4097) [ClassicSimilarity], result of:
0.07463435 = score(doc=4097,freq=2.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.31049973 = fieldWeight in 4097, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.046875 = fieldNorm(doc=4097)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- A challenge of managing and extracting useful knowledge from social media data sources has attracted much attention from academic and industry. To address this challenge, semantic analysis of textual data is focused in this paper. We propose an ontology-based approach to extract semantics of textual data and define the domain of data. In other words, we semantically analyse the social data at two levels i.e. the entity level and the domain level. We have chosen Twitter as a social channel challenge for a purpose of concept proof. Domain knowledge is captured in ontologies which are then used to enrich the semantics of tweets provided with specific semantic conceptual representation of entities that appear in the tweets. Case studies are used to demonstrate this approach. We experiment and evaluate our proposed approach with a public dataset collected from Twitter and from the politics domain. The ontology-based approach leverages entity extraction and concept mappings in terms of quantity and accuracy of concept identification.
-
Survey of text mining : clustering, classification, and retrieval (2004)
0.02
0.015548823 = product of:
0.031097647 = sum of:
0.031097647 = product of:
0.062195294 = sum of:
0.062195294 = weight(_text_:media in 804) [ClassicSimilarity], result of:
0.062195294 = score(doc=804,freq=2.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.25874978 = fieldWeight in 804, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.0390625 = fieldNorm(doc=804)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.
-
Tonkin, E.L.; Tourte, G.J.L.: Working with text. tools, techniques and approaches for text mining (2016)
0.02
0.015548823 = product of:
0.031097647 = sum of:
0.031097647 = product of:
0.062195294 = sum of:
0.062195294 = weight(_text_:media in 4019) [ClassicSimilarity], result of:
0.062195294 = score(doc=4019,freq=2.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.25874978 = fieldWeight in 4019, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.0390625 = fieldNorm(doc=4019)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Abstract
- What is text mining, and how can it be used? What relevance do these methods have to everyday work in information science and the digital humanities? How does one develop competences in text mining? Working with Text provides a series of cross-disciplinary perspectives on text mining and its applications. As text mining raises legal and ethical issues, the legal background of text mining and the responsibilities of the engineer are discussed in this book. Chapters provide an introduction to the use of the popular GATE text mining package with data drawn from social media, the use of text mining to support semantic search, the development of an authority system to support content tagging, and recent techniques in automatic language evaluation. Focused studies describe text mining on historical texts, automated indexing using constrained vocabularies, and the use of natural language processing to explore the climate science literature. Interviews are included that offer a glimpse into the real-life experience of working within commercial and academic text mining.
-
Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997)
0.01
0.013905852 = product of:
0.027811704 = sum of:
0.027811704 = product of:
0.05562341 = sum of:
0.05562341 = weight(_text_:22 in 1737) [ClassicSimilarity], result of:
0.05562341 = score(doc=1737,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.30952093 = fieldWeight in 1737, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=1737)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Date
- 22.11.1998 18:57:22
-
Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999)
0.01
0.013905852 = product of:
0.027811704 = sum of:
0.027811704 = product of:
0.05562341 = sum of:
0.05562341 = weight(_text_:22 in 4261) [ClassicSimilarity], result of:
0.05562341 = score(doc=4261,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.30952093 = fieldWeight in 4261, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=4261)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Date
- 17. 7.2002 19:22:06
-
Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997)
0.01
0.013905852 = product of:
0.027811704 = sum of:
0.027811704 = product of:
0.05562341 = sum of:
0.05562341 = weight(_text_:22 in 1270) [ClassicSimilarity], result of:
0.05562341 = score(doc=1270,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.30952093 = fieldWeight in 1270, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0625 = fieldNorm(doc=1270)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Source
- Information systems. 22(1997) nos.5/6, S.333-347
-
Mining text data (2012)
0.01
0.012439058 = product of:
0.024878116 = sum of:
0.024878116 = product of:
0.049756233 = sum of:
0.049756233 = weight(_text_:media in 362) [ClassicSimilarity], result of:
0.049756233 = score(doc=362,freq=2.0), product of:
0.24036849 = queryWeight, product of:
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.051318336 = queryNorm
0.20699982 = fieldWeight in 362, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
4.6838713 = idf(docFreq=1110, maxDocs=44218)
0.03125 = fieldNorm(doc=362)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Content
- Inhalt: An Introduction to Text Mining.- Information Extraction from Text.- A Survey of Text Summarization Techniques.- A Survey of Text Clustering Algorithms.- Dimensionality Reduction and Topic Modeling.- A Survey of Text Classification Algorithms.- Transfer Learning for Text Mining.- Probabilistic Models for Text Mining.- Mining Text Streams.- Translingual Mining from Text Data.- Text Mining in Multimedia.- Text Analytics in Social Media.- A Survey of Opinion Mining and Sentiment Analysis.- Biomedical Text Mining: A Survey of Recent Progress.- Index.
-
Hofstede, A.H.M. ter; Proper, H.A.; Van der Weide, T.P.: Exploiting fact verbalisation in conceptual information modelling (1997)
0.01
0.0121676205 = product of:
0.024335241 = sum of:
0.024335241 = product of:
0.048670482 = sum of:
0.048670482 = weight(_text_:22 in 2908) [ClassicSimilarity], result of:
0.048670482 = score(doc=2908,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.2708308 = fieldWeight in 2908, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.0546875 = fieldNorm(doc=2908)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Source
- Information systems. 22(1997) nos.5/6, S.349-385
-
Lackes, R.; Tillmanns, C.: Data Mining für die Unternehmenspraxis : Entscheidungshilfen und Fallstudien mit führenden Softwarelösungen (2006)
0.01
0.010429389 = product of:
0.020858778 = sum of:
0.020858778 = product of:
0.041717555 = sum of:
0.041717555 = weight(_text_:22 in 1383) [ClassicSimilarity], result of:
0.041717555 = score(doc=1383,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.23214069 = fieldWeight in 1383, 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=1383)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Date
- 22. 3.2008 14:46:06
-
Hallonsten, O.; Holmberg, D.: Analyzing structural stratification in the Swedish higher education system : data contextualization with policy-history analysis (2013)
0.01
0.008691157 = product of:
0.017382314 = sum of:
0.017382314 = product of:
0.03476463 = sum of:
0.03476463 = weight(_text_:22 in 668) [ClassicSimilarity], result of:
0.03476463 = score(doc=668,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.19345059 = fieldWeight in 668, 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=668)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Date
- 22. 3.2013 19:43:01
-
Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015)
0.01
0.008691157 = product of:
0.017382314 = sum of:
0.017382314 = product of:
0.03476463 = sum of:
0.03476463 = weight(_text_:22 in 1605) [ClassicSimilarity], result of:
0.03476463 = score(doc=1605,freq=2.0), product of:
0.17970806 = queryWeight, product of:
3.5018296 = idf(docFreq=3622, maxDocs=44218)
0.051318336 = queryNorm
0.19345059 = fieldWeight in 1605, 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=1605)
0.5 = coord(1/2)
0.5 = coord(1/2)
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
