A Study Using $n$-gram Features for Text Categorization
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[1] David D. Lewis,et al. Representation and Learning in Information Retrieval , 1991 .
[2] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .
[3] David D. Lewis,et al. Feature Selection and Feature Extraction for Text Categorization , 1992, HLT.
[4] David D. Lewis,et al. An evaluation of phrasal and clustered representations on a text categorization task , 1992, SIGIR '92.
[5] Johannes Fürnkranz,et al. Incremental Reduced Error Pruning , 1994, ICML.
[6] Ellen Riloff,et al. Little words can make a big difference for text classification , 1995, SIGIR '95.
[7] William W. Cohen. Fast Effective Rule Induction , 1995, ICML.
[8] William W. Cohen. Learning Trees and Rules with Set-Valued Features , 1996, AAAI/IAAI, Vol. 1.
[9] Heikki Mannila,et al. Fast Discovery of Association Rules , 1996, Advances in Knowledge Discovery and Data Mining.
[10] Yiming Yang,et al. A Comparative Study on Feature Selection in Text Categorization , 1997, ICML.
[11] Andrew McCallum,et al. A comparison of event models for naive bayes text classification , 1998, AAAI 1998.
[12] Ellen Riloff,et al. A Case Study in Using Linguistic Phrases for Text Categorization on the WWW , 1998 .
[13] Dunja Mladenic,et al. Word sequences as features in text-learning , 1998 .
[14] Dunja Mladenic,et al. Feature Subset Selection in Text-Learning , 1998, ECML.