Lazy learner text categorization algorithm based on embedded feature selection

Journal of Systems Engineering and Electronics

Volumn 20, Issue 3, 2009, Pages 651-659

  Yan, Peng ^a,b   Zheng, Xuefeng ^a   Zhu, Jianyong ^b   Xiao, Yunhong ^a  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY BEIJING   (China)

^b China State Information Center   (China)

Author keywords

Cosine similarity; Embedded feature selection; Lazy learner; Machine learning; Text categorization

Indexed keywords

COSINE SIMILARITY; EMBEDDED FEATURE SELECTION; LAZY LEARNERS; MACHINE-LEARNING; TEXT CATEGORIZATION;

ALGORITHMS; FEATURE EXTRACTION; TEXT PROCESSING; THERMAL CONDUCTIVITY;

LEARNING SYSTEMS;

EID: 77957565222     PISSN: 10044132     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (9)

1. Mitchell T M. Machine learning. Beijing: China Machine Press, 2003: 165-178.
2. Tan P, Stenbach M, Kumar V. Introduction to data mining. Beijing: People Posts & Telecom Press, 2006: 13-50, 137-150.
3. Yang Y, Pedersen J. A comparative study on feature selection in text categorization. San Francisco: Morgan Kaufmann Publishers, 1997.
4. Delanya S J, Pádraig Cunninghamb. An analysis of casebase editing in a spam filtering system. Computer Science. 2004, 3155: 128-141.
5. Stone T. Parameterization of naive bayes for spam filtering. University of Colorado at Boulder, 2003.
6. Zorkadis V, Karras D A, Panayotou M. Efficient information theoretic strategies for classifier combination: feature extraction and performance evaluation in improving false positives and false negatives for spam e-mail filtering. Neural Networks, 2005, 18: 799-807.
7. Delany S J, Pádraig Cunningham, Coyle L. An Assessment of case-based reasoning for spam filtering. Artificial Intelligence Review, 2005, 24(3-4): 359-378. (Pubitemid 41813390)
8. Delanya S J, Pádraig Cunninghamb, Tsymbalb A, et al. A case-based technique for tracking concept drift in spam filtering. Knowledge-Based Systems, 2005, 18(4-5): 187-195.
9. Androutsopoulos I, Koutsias J, Chandrinos K V, et al. An evaluation of naive bayesian anti-spam filtering. Proc. of the workshop on Machine Learning in the New Information Age, Barcelona, Spain, 2000.