-
Pfister, J.: Clustering von Patent-Dokumenten am Beispiel der Datenbanken des Fachinformationszentrums Karlsruhe (2006)
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- Source
- Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
-
Bock, H.-H.: Datenanalyse zur Strukturierung und Ordnung von Information (1989)
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- Pages
- S.1-22
-
Dubin, D.: Dimensions and discriminability (1998)
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- Date
- 22. 9.1997 19:16:05
-
Automatic classification research at OCLC (2002)
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- Date
- 5. 5.2003 9:22:09
-
Yi, K.: Automatic text classification using library classification schemes : trends, issues and challenges (2007)
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- Date
- 22. 9.2008 18:31:54
-
Díaz, I.; Ranilla, J.; Montañes, E.; Fernández, J.; Combarro, E.F.: Improving performance of text categorization by combining filtering and support vector machines (2004)
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-
Na, J.-C.; Sui, H.; Khoo, C.; Chan, S.; Zhou, Y.: Effectiveness of simple linguistic processing in automatic sentiment classification of product reviews (2004)
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-
Qu, B.; Cong, G.; Li, C.; Sun, A.; Chen, H.: ¬An evaluation of classification models for question topic categorization (2012)
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- Abstract
- We study the problem of question topic classification using a very large real-world Community Question Answering (CQA) dataset from Yahoo! Answers. The dataset comprises 3.9 million questions and these questions are organized into more than 1,000 categories in a hierarchy. To the best knowledge, this is the first systematic evaluation of the performance of different classification methods on question topic classification as well as short texts. Specifically, we empirically evaluate the following in classifying questions into CQA categories: (a) the usefulness of n-gram features and bag-of-word features; (b) the performance of three standard classification algorithms (naive Bayes, maximum entropy, and support vector machines); (c) the performance of the state-of-the-art hierarchical classification algorithms; (d) the effect of training data size on performance; and (e) the effectiveness of the different components of CQA data, including subject, content, asker, and the best answer. The experimental results show what aspects are important for question topic classification in terms of both effectiveness and efficiency. We believe that the experimental findings from this study will be useful in real-world classification problems.
-
Bianchini, C.; Bargioni, S.: Automated classification using linked open data : a case study on faceted classification and Wikidata (2021)
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-
Liu, R.-L.: Context recognition for hierarchical text classification (2009)
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- Date
- 22. 3.2009 19:11:54
-
Pfeffer, M.: Automatische Vergabe von RVK-Notationen mittels fallbasiertem Schließen (2009)
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- Date
- 22. 8.2009 19:51:28
-
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
-
Wu, K.J.; Chen, M.-C.; Sun, Y.: Automatic topics discovery from hyperlinked documents (2004)
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Hung, C.-M.; Chien, L.-F.: Web-based text classification in the absence of manually labeled training documents (2007)
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-
Montesi, M.; Navarrete, T.: Classifying web genres in context : A case study documenting the web genres used by a software engineer (2008)
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- Abstract
- This case study analyzes the Internet-based resources that a software engineer uses in his daily work. Methodologically, we studied the web browser history of the participant, classifying all the web pages he had seen over a period of 12 days into web genres. We interviewed him before and after the analysis of the web browser history. In the first interview, he spoke about his general information behavior; in the second, he commented on each web genre, explaining why and how he used them. As a result, three approaches allow us to describe the set of 23 web genres obtained: (a) the purposes they serve for the participant; (b) the role they play in the various work and search phases; (c) and the way they are used in combination with each other. Further observations concern the way the participant assesses quality of web-based resources, and his information behavior as a software engineer.
-
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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-
Alberts, I.; Forest, D.: Email pragmatics and automatic classification : a study in the organizational context (2012)
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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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-
Mengle, S.; Goharian, N.: Passage detection using text classification (2009)
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- Date
- 22. 3.2009 19:14:43
