High-order concept associations mining and inferential language modeling for online review spam detection

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2010, Pages 1120-1127

  Lai, C L ^a   Xu, K Q ^a   Lau, Raymond Y K ^a   Li, Yuefeng ^b   Song, Dawei ^c  

^a CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^b QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^c ROBERT GORDON UNIVERSITY   (United Kingdom)

Author keywords

Kullback leibler divergence; Language modeling; Review spam; Spam detection; Text mining

Indexed keywords

COMPUTATIONAL LINGUISTICS; DATA MINING; ELECTRONIC COMMERCE; NATURAL LANGUAGE PROCESSING SYSTEMS;

KULLBACK LEIBLER DIVERGENCE; LANGUAGE MODEL; REVIEW SPAM; SPAM DETECTION; TEXT MINING;

MODELING LANGUAGES;

EID: 84988299645     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2010.30     Document Type: Conference Paper

References (33)

1. R. Agrawal and R. Srikant. Fast algorithms for mining association rules in large databases. In J. B. Bocca, M. Jarke, and C. Zaniolo, editors, VLDB'94, Proceedings of 20th International Conference on Very Large Data Bases, pages 487-499.
2. A. Bratko, B. Filipi, G. Cormack, T. Lynam, and B. Zupan. Spam filtering using statistical data compression models. The Journal of Machine Learning Research, 7:2673-2698, 2006. (Pubitemid 46011492)
3. M. Chang, W. Yih, and C. Meek. Partitioned logistic regression for spam filtering. In Proceeding of the 14th ACM SIGKDD'08, pages 97-105. ACM, 2008.
4. F. Chen, P. Tan, and A. Jain. A co-classification framework for detecting web spam and spammers in social media web sites. In Proceeding of the 18th ACM CIKM, pages 1807- 1810. ACM, 2009.
5. M. Cheung, C. Luo, C. Sia, and H. Chen. Credibility of electronic word-of-mouth: Informational and normative determinants of on-line consumer recommendations. International Journal of Electronic Commerce, 13:9-38, 2009.
6. G. Cormack. Spam Track Overview. In E. Voorhees, editor, Proceedings of the Sixteenth Text REtrieval Conference, Gaithersburg, Maryland, 2007. NIST. Available from http://trec.nist.gov/pubs/trec16/papers.
7. G. Cormack, J. Hidalgo, and E. Sánz. Online supervised spam filter evaluation. ACM Transactions on Information Systems, 25:11.1-11.31, 2007.
8. G. Cormack, J. Hidalgo, and E. Sánz. Spam filtering for short messages. In Proceeding of the 16th ACM CIKM, pages 313- 319. ACM, 2007.
9. C. Danescu-Niculescu-Mizil, G. Kossinets, J. Kleinberg, and L. Lee. How opinions are received by online communities: a case study on amazon.com helpfulness votes. In Proceedings of the 18th WWW Conference, pages 141-150. ACM, 2009.
10. C. Dellarocas. Strategic manipulation of internet opinion forums: Implications for consumers and firms. Management Science, 52:1577-1593, 2006. (Pubitemid 44556062)
11. D. Fetterly, M. Manasse, and M. Najork. Detecting phraselevel duplication on the world wide web. In Proceedings of the 28th Annual International ACM SIGIR Conference, pages 170-177, Salvador, Brazil, Aug.15-19 2005. ACM.
12. N. Jindal and B. Liu. Analyzing and detecting review spam. In Proceedings of the Seventh IEEE International Conference on Data Mining, pages 547-552, 2007.
13. N. Jindal and B. Liu. Review spam detection. In Proceedings of the 16th International Conference on World Wide Web, pages 1189-1190, 2007. (Pubitemid 47582376)
14. N. Jindal and B. Liu. Opinion spam and analysis. In Proceedings of the 2008 international conference on Web search and web data mining, pages 219-229, 2008. (Pubitemid 351588793)
15. T. Joachims. Making large-scale svm learning practical. In B. Schölkopf, C. J. C. Burges, and A. J. Smola, editors, Advances in Kernel Methods - Support Vector Learning. MIT Press, Cambridge, Massachusetts, 1999.
16. S. Kullback and R. A. Leibler. On information and sufficiency. The Annals of Mathematical Statistics, 22:79-86, 1951.
17. J. Lafferty and C. Zhai. Document language models, query models, and risk minimization for information retrieval. In Proceedings of the 24th annual international ACM SIGIR conference, pages 111-119, 2001. (Pubitemid 32951063)
18. R. Lau. Context-Sensitive Text Mining and Belief Revision for Intelligent Information Retrieval on theWeb. Web Intelligence and Agent Systems An International Journal, 1(3-4):1- 22, 2003.
19. R. Lau, P. Bruza, and D. Song. Towards a Belief Revision Based Adaptive and Context-Sensitive Information Retrieval System. ACM Transactions on Information Systems, 26(2):8.1-8.38, 2008.
20. R. Lau, C. Lai, and Y. Li. Leveraging the web context for context-sensitive opinion mining. In Proceedings of the 2009 IEEE International Conference on Computer Science and Information Technology, pages 467-471. IEEE, 2009.
21. R. Lau, D. Song, Y. Li, C. Cheung, and J. Hao. Towards A Fuzzy Domain Ontology Extraction Method for Adaptive e-Learning. IEEE Transactions on Knowledge and Data Engineering, 21(6):800-813, 2009.
22. X. Liu and B. Croft. Cluster-based retrieval using language models. In Proceedings of the 27th Annual International ACM SIGIR Conference, pages 186-193, 2004.
23. J. Martinez-Romo and L. Araujo. Web spam identification through language model analysis. In Proceedings of the Fifth International Workshop on Adversarial Information Retrieval on the Web, pages 21-28, 2009.
24. G. A. Miller, B. R., C. Fellbaum, D. Gross, and K. J. Miller. Introduction to wordnet: An on-line lexical database. Journal of Lexicography, 3(4):234-244, 1990.
25. G. Mishne, D. Carmel, and R. Lempel. Blocking blog spam with language model disagreement. In Proceedings of the First International Workshop on Adversarial Information Retrieval on the Web, pages 1-6, 2005.
26. J.-Y. Nie, G. Cao, and J. Bai. Inferential language models for information retrieval. ACM Transactions on Asian Language Information Processing, 5(4):296-322, Dec. 2006. (Pubitemid 46580875)
27. P. Perrin and F. Petry. Extraction and representation of contextual information for knowledge discovery in texts. Information Sciences, 151:125-152, 2003.
28. J. M. Ponte and W. B. Croft. A language modeling approach to information retrieval. In Proceedings of the 21st Annual International ACM SIGIR Conference, pages 275-281, Melbourne, Australia, 1998.
29. G. Salton and M. McGill. Introduction to Modern Information Retrieval. McGraw-Hill, New York, New York, 1983.
30. M. Sanderson and B. Croft. Deriving concept hierarchies from text. In Proceedings of the 22nd Annual International ACM SIGIR Conference, pages 206-213. ACM, 1999.
31. C. Shannon. A mathematical theory of communication. Bell System Technology Journal, 27:379-423, 1948.
32. C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to information retrieval. ACM Transactions on Information Systems, 22:179-214, 2004.
33. E. Zheleva, A. Kolcz, and L. Getoor. Trusting spam reporters: A reporter-based reputation system for email filtering. ACM Transactions on Information Systems, 27:3.1-3.38, 2008.