Exploiting user feedback to learn to rank answers in Q&A forums: A case study with stack overflow

SIGIR 2013 - Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2013, Pages 543-552

  Dalip, Daniel Hasan ^a   Gonçalves, Marcos André ^a   Cristo, Marco ^b   Calado, Pável ^c  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b FEDERAL UNIVERSITY OF AMAZONAS   (Brazil)

^c INSTITUTO SUPERIOR TÉCNICO   (Portugal)

Author keywords

Answer Quality; Content Quality Assessment; Learning to Rank; Q A Forums

Indexed keywords

ASSESSMENT STRATEGIES; COLLABORATIVE WEBS; CONTENT QUALITIES; CONTROL MECHANISM; LEARNING TO RANK; QUALITY RANKING; RANDOM FORESTS; STATE OF THE ART;

DECISION TREES; INFORMATION RETRIEVAL; QUERY PROCESSING; RESEARCH;

QUALITY CONTROL;

EID: 84883080392     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2484028.2484072     Document Type: Conference Paper

References (34)

1. Automatic identification of best answers in online enquiry communities. In G. Burel, Y. He, and H. Alani, editors, 9th Extended Semantic Web Conference, Volume 7295 of Lecture Notes in Computer Science, Crete, 2012. Springer Berlin Heidelberg.
2. E. Agichtein, C. Castillo, D. Donato, A. Gionis, and G. Mishne. Finding high-quality content in social media. In WSDM '08, pages 183-194, Palo Alto, California, USA, 2008. ACM.
3. A. Anderson, D. Huttenlocher, J. Kleinberg, and J. Leskovec. Discovering Value from Community Activity on Focused Question Answering Sites: A Case Study of Stack Overflow. In KDD'12, 2012.
4. G. Attardi, F. dell'Orletta, M. Simi, A. Chanev, and M. Ciaramita. Multilingual dependency parsing and domain adaptation using desr. In EMNLP-CoNLL, pages 1112-1118, 2007.
5. C. Björnsson. Lesbarkeit durch Lix. Stockholm: Pedagogiskt Centrum, 1968.
6. L. Breiman. Random forests. Mach. Learn., 45(1):5-32, Oct. 2001.
7. S. L. Cessie and J. V. Houwelingen. Ridge estimators in logistic regression. Journal of the Royal Statistical Society. Series C, 41(1):191-201, 1992.
8. M. Ciaramita and Y. Altun. Broad-coverage sense disambiguation and information extraction with a supersense sequence tagger. In EMNLP '06, EMNLP '06, pages 594-602, Stroudsburg, PA, USA, 2006. Association for Computational Linguistics.
9. M. Coleman and T. L. Liau. A computer readability formula designed for machine scoring. Journal of Applied Psychology, 60(2):283-284, 1975.
10. D. H. Dalip, M. A. Gonçalves, M. Cristo, and P. Calado. Automatic assessment of document quality in web collaborative digital libraries. ACM Journal of Data and Information Quality, 2(13), 2011.
11. R. Flesch. A new readability yardstick. Journal of Applied Psychology, pages 221-235, 1948.
12. Y. Freund and L. Mason. The alternating decision tree learning algorithm. In ICML'99, 1999.
13. J. H. Friedman. Stochastic gradient boosting. Computational Statistics & Data Analysis, 38(4):367-378, Feb. 2002.
14. R. Gunning. The Technique of Clear Writing. McGraw-Hill International Book Co, 1952.
15. K. Järvelin and J. Kekäläinen. IR evaluation methods for retrieving highly relevant documents. In SIGIR '00, pages 41-48, Athens, Greece, 2000.
16. J. Jeon, W. B. Croft, J. H. Lee, and S. Park. A framework to predict the quality of answers with non-textual features. In SIGIR '06, pages 228-235, Seattle, Washington, USA, 2006. ACM.
17. J. M. Kleinberg. Hubs, authorities, and communities. ACM Comput. Surv., 31(4es), Dec. 1999.
18. S. Kullback and R. A. Leibler. On information and sufficiency. The Annals of Mathematical Statistics, 22(1):79-86, 1951.
19. B. Li, T. Jin, M. R. Lyu, I. King, B. Mak, T. Chinese, and H. Kong. Analyzing and Predicting Question Quality in Community Question Answering Services Categories and Subject Descriptors. pages 775-782, 2012.
20. G. H. McLaughlin. Smog grading: A new readability formula. Journal of Reading, pages 639-646, 1969.
21. T. M. Mitchell. Machine Learning. McGraw-Hill Higher Education, 1997.
22. A. Mohan, Z. Chen, and K. Weinberger. Web-search ranking with initialized gradient boosted regression trees. JMLR Workshop and Conference Proceedings: Proceedings of the Yahoo! Learning to Rank Challenge, 14:77-89, June 2011.
23. L. Page, S. Brin, R. Motwani, and T. Winograd. The PageRank Citation Ranking: Bringing Order to the Web. Technical report, Stanford Digital Library Technologies Project, 1998.
24. L. Rassbach, T. Pincock, and B. Mingus. Exploring the feasibility of automatically rating online article quality. http://upload.wikimedia.org/ wikipedia/wikimania2007/d/d3/RassbachPincockMingus07.pdf, 2007.
25. S. Ressler. Perspectives on electronic publishing: standards, solutions, and more. Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1993.
26. S. E. Robertson and S. Walker. Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval. In SIGIR '94, SIGIR '94, pages 232-241, New York, NY, USA, 1994. Springer-Verlag New York, Inc.
27. T. Sakai, D. Ishikawa, N. Kando, Y. Seki, K. Kuriyama, and C.-Y. Lin. Using graded-relevance metrics for evaluating community QA answer selection. In WSDM '11, page 187, New York, New York, USA, Feb. 2011. ACM Press.
28. C. Shah and J. Pomerantz. Evaluating and predicting answer quality in community QA. In SIGIR'10, number March 2008, 2010.
29. E. A. Smith and R. J. Senter. Automated readability index. Aerospace Medical Division, 1967.
30. B. Stvilia, M. B. Twidale, L. C. Smith, and L. Gasser. Assessing information quality of a community-based encyclopedia. In ICIQ'05, pages 442-454, 2005.
31. M. Surdeanu, M. Ciaramita, and H. Zaragoza. Learning to Rank Answers on Large Online QA Collections. ACL '08, 2008.
32. M. A. Suryanto and R. H. L. Chiang. Quality-Aware Collaborative Question Answering: Methods and Evaluation. In WSDM '09, pages 142-151, 2009.
33. F. Wilcoxon. Individual comparisons by ranking methods. Biometrics, pages 80-83, 1945.
34. J. Zhang, M. S. Ackerman, and L. Adamic. Expertise networks in online communities. In WWW '07, New York, New York, USA, 2007. ACM Press.