An information gain-based approach for recommending useful product reviews

1. Anagnostopoulos A, Broder AZ, Punera K (2008) Effective and efficient classification on a search-engine model. Knowl Inf Syst 16(2): 129–154

   Article  Google Scholar 

2. Balabanovic M (1997) An adaptive web page recommendation service. In: Proceedings of the first international conference on autonomous agents, pp 378–385

3. Euzenat J (2007) Semantic precision and recall for ontology alignment evaluation. In: Proceedings of the 2007 international joint conference on artificial intelligence, pp 348–353

4. Goldberg D, Nichols D, Oki BM, Terry D (1992) Using collaborative filtering to weave an information tapestry. Commun ACM 35(12): 61–70

   Article  Google Scholar 

5. Hatzivassiloglou V, McKeown KR (1997) Predicting the semantic orientation of adjectives. In: Proceedings of the eighth conference on European chapter of the association for computational linguistics, pp 174–181

6. Hu M, Liu B (2004) Mining and summarizing customer reviews. In: Proceedings of the tenth ACM international conference on knowledge discovery and data mining, pp 168–177

7. Hu N, Liu L, Zhang J (2008) Do online reviews affect product sales? The role of reviewer characteristics and temporal effects. Inf Technol Manag

8. Inui K, Abe S, Hara K, Morita H, Sao C, Eguchi M, Sumida A, Murakami K, Matsuyoshi S (2008) Experience mining: building a large-scale database of personal experiences and opinions from Web documents. In: Proceedings of the 2008 IEEE/WIC/ACM international conference on web intelligence and intelligent agent technology, pp 314–321

9. Kim SM, Pantel P, Chklovski T, Pennacchiotti M (2006) Automatically assessing review helpfulness. In: Proceedings of the 2006 Conference on empirical methods in natural language processing, pp 423–430

10. Lee C, Lee GG (2006) Information gain and divergence-based feature selection for machine learning-based text categorization. Inform Process Manag 42

11. Pang B, Lee L, Vaithyanathan S (2002) Thumbs up?: sentiment classification using machine learning techniques. In: Proceedings of the ACL-02 conference on empirical methods in natural language processing, pp 79–86

12. Park DH, Lee J, Han I (2007) The effect of on-line consumer reviews on consumer purchasing intention: the moderating role of involvement. Int J Electron Commerce 11(4): 125–148

    Article  Google Scholar 

13. Pollach I (2006) Electronic word of mouth: a genre analysis of product reviews on consumer opinion web sites. HICSS 3: 1530–1605

    Google Scholar 

14. Resnick P, Iacovou N, Suchak M, Bergstrom P, Riedl J (1994) GroupLens: an open architecture for collaborative filtering of netnews. In: Proceedings of the 1994 ACM conference on computer supported cooperative work, pp 175–186

15. Sarwar BM, Karypis G, Konstan JA, Reidl J (2001) Item-based collaborative filtering recommendation algorithms. World Wide Web pp 285–295

16. Shannon CE (2001) A mathematical theory of communication. SIGMOBILE Mob Comput Commun Rev 5(1): 3–55

    Article  Google Scholar 

17. Turney P (2002) Thumbs up or thumbs down? semantic orientation applied to unsupervised classification of reviews. In: Proceedings of the 40th annual meeting of the association for computational linguistics (ACL), pp 417–424

18. Weimer M, Gurevych I, Mühlhäuser M (2007) Automatically assessing the post quality in online discussions on software. In: Proceedings of the 45th annual meeting of the association for computational linguistics, pp 125–128

19. Weimer M, Gurevych I (2007) Predicting the perceived quality of web forum posts. In: Proceedings of the conference on recent advances in natural language processing

20. Wong T, Lam W (2008) Learning to extract and summarize hot item features from multiple auction web sites. Knowl Inf Syst 14(2): 143–160

    Article  Google Scholar 

21. Wu X, Kumar V, Quinlan J, Ghosh J, Yang Q, Motoda H, McLachlan GJ, Ng A, Liu B, Yu PS, Zhou Z, Steinbach M, Hand DJ, Steinberg D (2008) Top 10 algorithms in data mining. Knowl Inf Syst 14(1): 1–37

    Article  Google Scholar 

22. Yang Y, Pedersen JO (1997) A comparative study on feature selection in text categorization. In: Proceedings of the fourteenth international conference on machine learning, pp 412–420

23. Yu H, Hatzivassiloglou V (2003) Toward answering opinion questions: separating facts from opinions and identifying the polarity of opinion sentences. In: Proceedings of the 2003 conference on empirical methods in natural language processing, pp 129–136

24. Zhuang L, Jing F, Zhu XY (2006) Movie review mining and summarization. In: Proceedings of the 15th ACM international conference on information and knowledge management, pp 43–50

Download references