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Liu, R.-L.: Context-based term frequency assessment for text classification (2010)
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- Abstract
- Automatic text classification (TC) is essential for the management of information. To properly classify a document d, it is essential to identify the semantics of each term t in d, while the semantics heavily depend on context (neighboring terms) of t in d. Therefore, we present a technique CTFA (Context-based Term Frequency Assessment) that improves text classifiers by considering term contexts in test documents. The results of the term context recognition are used to assess term frequencies of terms, and hence CTFA may easily work with various kinds of text classifiers that base their TC decisions on term frequencies, without needing to modify the classifiers. Moreover, CTFA is efficient, and neither huge memory nor domain-specific knowledge is required. Empirical results show that CTFA successfully enhances performance of several kinds of text classifiers on different experimental data.
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Jersek, T.: Automatische DDC-Klassifizierung mit Lingo : Vorgehensweise und Ergebnisse (2012)
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HaCohen-Kerner, Y. et al.: Classification using various machine learning methods and combinations of key-phrases and visual features (2016)
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- Date
- 1. 2.2016 18:25:22
-
Schaalje, G.B.; Blades, N.J.; Funai, T.: ¬An open-set size-adjusted Bayesian classifier for authorship attribution (2013)
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Sojka, P.; Lee, M.; Rehurek, R.; Hatlapatka, R.; Kucbel, M.; Bouche, T.; Goutorbe, C.; Anghelache, R.; Wojciechowski, K.: Toolset for entity and semantic associations : Final Release (2013)
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Fagni, T.; Sebastiani, F.: Selecting negative examples for hierarchical text classification: An experimental comparison (2010)
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Barthel, S.; Tönnies, S.; Balke, W.-T.: Large-scale experiments for mathematical document classification (2013)
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Mu, T.; Goulermas, J.Y.; Korkontzelos, I.; Ananiadou, S.: Descriptive document clustering via discriminant learning in a co-embedded space of multilevel similarities (2016)
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Salles, T.; Rocha, L.; Gonçalves, M.A.; Almeida, J.M.; Mourão, F.; Meira Jr., W.; Viegas, F.: ¬A quantitative analysis of the temporal effects on automatic text classification (2016)
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Yilmaz, T.; Ozcan, R.; Altingovde, I.S.; Ulusoy, Ö.: Improving educational web search for question-like queries through subject classification (2019)
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Ru, C.; Tang, J.; Li, S.; Xie, S.; Wang, T.: Using semantic similarity to reduce wrong labels in distant supervision for relation extraction (2018)
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Zhu, W.Z.; Allen, R.B.: Document clustering using the LSI subspace signature model (2013)
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- Date
- 23. 3.2013 13:22:36
-
Egbert, J.; Biber, D.; Davies, M.: Developing a bottom-up, user-based method of web register classification (2015)
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- Date
- 4. 8.2015 19:22:04
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Groß, T.; Faden, M.: Automatische Indexierung elektronischer Dokumente an der Deutschen Zentralbibliothek für Wirtschaftswissenschaften : Bericht über die Jahrestagung der Internationalen Buchwissenschaftlichen Gesellschaft (2010)
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Liu, R.-L.: ¬A passage extractor for classification of disease aspect information (2013)
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- Date
- 28.10.2013 19:22:57
