Effective and efficient classification on a search-engine model

Knowledge and Information Systems

Volumn 16, Issue 2, 2008, Pages 129-154

  Anagnostopoulos, Aris ^a   Broder, Andrei ^a   Punera, Kunal ^b  

^a YAHOO RESEARCH   (United States)

^b The University of Texas at Austin   (United States)

Author keywords

Feature selection; Query efficiency; Search engine; Term correlations; Text classification; WAND

Indexed keywords

CLASSIFICATION (OF INFORMATION); EFFICIENCY; FEATURE EXTRACTION; SEARCH ENGINES; SUPPORT VECTOR MACHINES; TEXT PROCESSING;

CLASSIFICATION ACCURACY; DOCUMENT CLASSIFICATION; LARGE DOCUMENT CORPORA; QUERY EFFICIENCY; SELECTION TECHNIQUES; TERM CORRELATIONS; TEXT CLASSIFICATION; WAND;

INFORMATION RETRIEVAL SYSTEMS;

EID: 48749119635     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-007-0102-6     Document Type: Article

References (26)

1. Baeza-Yates R and Ribeiro-Neto B (1999). Modern information retrieval. Addison, Wesley, Reading
2. Broder AZ, Carmel D, Herscovici M, Soffer A, Zien J (2003) Efficient query evaluation using a two-level retrieval process. In: Proceedings of the 12th International conference on information and knowledge management, pp 426-434
3. Carmel D, Amitay E, Herscovici M, Maarek YS, Petruschka Y, Soffer A (2001) Juru at TREC 10 - Experiments with Index Pruning. In: Proceedings of the 10th Text REtrieval Conference (TREC), NIST
4. Chakrabarti S, Dom B, Agrawal R and Raghavan P (1998). Scalable feature selection, classification and signature generation for organizing large text databases into hierarchical topic taxonomies. VLDB J 7(3):163-178
5. Chang C-H and Hsu C-C (1999). Enabling concept-based relevance feedback for information retrieval on the WWW. IEEE Trans Knowl Data Eng 11(4):595-609
6. Domingos P and Pazzani MJ (1997). On the optimality of the simple Bayesian classifier under zero-one loss. Mach Learn 29(2-3):103-130
7. Fawcett T (2003) ROC graphs: Notes and practical considerations for data mining researchers. Technical Report HPL-2003-4, HP Laboratories
8. Flake GW, Glover EJ, Lawrence S, Giles CL (2002) Extracting query modifications from nonlinear SVMs. In: Proceedigs of the 11th International conference on World Wide Web, pp 317-324
9. Friedman JH (1997). On bias, variance, 01 loss and the curse-of-dimensionality. Data Mining Knowl Discov 1(1):55-77
10. Glover EJ, Flake GW, Lawrence S, Birmingham WP, Kruger A, Giles CL, Pennock D (2001) Improving category specific web search by learning query modifications. In: Symposium on Applications and the Internet, SAINT, pp 23-31
11. Haines D, Croft WB (1993) Relevance feedback and inference networks. In: Proceedings of the 16th ACM SIGIR conference on research and development in information retrieval, pp 2-11
12. Hancock-Beaulieu M, Gatford M, Huang X, Robertson SE, Walker S, Williams PW (1997) Okapi at trec. In: 5th Text REtrieval Conference (TREC)
13. Joachims T (1998) Text categorization with support vector machines: Learning with many relevant features. In: Proceedings of 10th European conference on machine learning, pp 137-142
14. Lewis DD, Yang Y, Rose TG and Li F (2004). RCV1: A new benchmark collection for text categorization research. J Mach Learn Res 5:361-397
15. McCallum A, Nigam K (1998) A comparison of event models for Naive Bayes text classification. In: AAAI-98 Workshop on Learning for Text Categorization
16. Mitchell T (1997). Machine learning. McGraw Hill, New York
17. Porter MF (1997) An algorithm for suffix stripping, pp 313-316
18. Quinlan JR (1993). C4.5: Programs for machine learning. Morgan Kaufmann, San Francisco
19. Rennie J, Rifkin R (2001) Improving multiclass text classification with the support vector machine. In: Massachusetts Institute of Technology. AI Memo AIM-2001-026
20. Rifkin R and Klautau A (2004). In defense of one-vs-all classification. J Mach Learn Res 5:101-141
21. Robertson SE and Jones KS (1976). Relevance weighting of search terms. J Am Soc Inform Sci 27:129-146
22. Rocchio JJ (1971). Relevance feedback in information retrieval. In: Salton, G (eds) The SMART retrieval system: Experiments in automatic document processing., pp 313-323. Prentice-Hall, Englewood cliffs
23. Salton G, Buckley C, Yu CT (1982) An evaluation of term dependence models in information retrieval. In: SIGIR, pp 151-173
24. Vapnik V (1995). The nature of statistical learning theory. Springer, Berlin
25. Yang Y, Liu X (1999) A re-examination of text categorization methods. In: Proceedings of the 22nd ACM SIGIR conference on research and development in information retrieval, pp 42-49
26. Yang Y, Pedersen J (1997) A comparative study on feature selection in text categorization. In: Proceedings of the 14th international conference on machine learning, pp 412-420