C4.5: programs for machine learning
C4.5: programs for machine learning
A maximum entropy approach to natural language processing
Computational Linguistics
Automatic classification of e-mail messages by messages type
Journal of the American Society for Information Science
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Conversation and Community: Chat in a Virtual World
Conversation and Community: Chat in a Virtual World
Machine Learning
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Comparative Study on Feature Selection in Text Categorization
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Automatic detection of text genre
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Recognizing text genres with simple metrics using discriminant analysis
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 2
Text genre detection using common word frequencies
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Towards genre classification for IR in the workplace
IIiX Proceedings of the 1st international conference on Information interaction in context
Genre identification and goal-focused summarization
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Is Web Genre Identification Feasible?
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Learning to recognize webpage genres
Information Processing and Management: an International Journal
Using non-lexical features to identify effective indexing terms for biomedical illustrations
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Unsupervised activity recognition using automatically mined common sense
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Wikipedia-based semantic interpretation for natural language processing
Journal of Artificial Intelligence Research
Genre distinctions for discourse in the Penn TreeBank
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
We're not in Kansas anymore: detecting domain changes in streams
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Accessibility summarization & simplification in a template-based web transcoder
Journal of Web Engineering
Structured text retrieval by means of affordances and genre
FDIA'07 Proceedings of the 1st BCS IRSG conference on Future Directions in Information Access
Building a document genre corpus: a profile of the KRYS I corpus
IRSG'08 Proceedings of the 2008 BCS-IRSG conference on Corpus Profiling
Toward automatically assembling Hittite-language cuneiform tablet fragments into larger texts
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
You have e-mail, what happens next? Tracking the eyes for genre
Information Processing and Management: an International Journal
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Categorization of text in IR has traditionally focused on topic. As use of the Internet and e-mail increases, categorization has become a key area of research as users demand methods of prioritizing documents. This work investigates text classification by format style, i.e. "genre", and demonstrates, by complementing topic classification, that it can significantly improve retrieval of information. The paper compares use of presentation features to word features, and the combination thereof, using Naïve Bayes, C4.5 and SVM classifiers. Results show use of combined feature sets with SVM yields 92% classification accuracy in sorting seven genres.