Demographic prediction based on user's browsing behavior

16th International World Wide Web Conference, WWW2007

Volumn , Issue , 2007, Pages 151-160

  Hu, Jian ^a   Zeng, Hua Jun ^a   Li, Hua ^a   Niu, Cheng ^a   Chen, Zheng ^a  

^a MICROSOFT RESEARCH ASIA   (China)

Author keywords

Browsing behavior; Demographic prediction; Singular value decomposition; Supervised regression

Indexed keywords

BAYESIAN NETWORKS; DATA REDUCTION; INFORMATION ANALYSIS; REGRESSION ANALYSIS; SINGULAR VALUE DECOMPOSITION; WEB BROWSERS;

BROWSING BEHAVIOR; DEMOGRAPHIC PREDICTION; SUPERVISED REGRESSION;

USER INTERFACES;

EID: 35348815641     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1242572.1242594     Document Type: Conference Paper

References (31)

1. Berryman-Fink, C. L., J. R. Wilcox (1983). A multivariate investigation of perceptual attributions concerning gender appropriateness in language, Sex Roles 9, 1983.
2. Biber, D., S. Conrad, R. Reppen (1998). Corpus Linguistics Investigating Language Structure and Use, Cambridge University Press, Cambridge, 1998.
3. Computerworld Report: Men Want Facts, Women Seek Personal Connections on Web, http://www.computerworld.com/developmenttopics/websitemgmt/story/0,10801, 107391p2,00.html.
4. Eckert, P. (1997). Gender and sociolinguistic variation, in J. Coates ed., Readings in Language and Gender, Blackwell, Oxford 1997, pp. 64-75.
5. Herring, S. (1996). Two variants of an electronic message schema, in S. Herring ed., Computer-Mediated Communication: Linguistic, Social and Cross-Cultural Perspectives (John Benjamins, Amsterdam, 1996), pp. 81-106.
6. Holmes, J. (1993). Women's talk: The question of sociolinguistic universais, Australian Journal of Communications 20, 3, 1993.
7. Google Personal, http://labs.google.com/personalized.
8. J. S. Breese, D. Heckerman, and C. Kadie. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the Fourteenth Annual Conference on Uncertainty in Artificial Intelligence, pages 43-52. Morgan Kaufman, 1998.
9. Lakoff, R. T. (1975). Language and Women's Place, Harper Colophon Books, New York, 1975.
10. Lewis, D., R. Schapire, J. Callan, R. Papka (1996). Training algorithms for text classifiers, in Proc. 19th ACM/SIGIR Conf. on R&D in IR, 1996, pp 306-298.
11. M. Koppel, J. Schler, S. Argamon, and J.W. Pennebaker. Effects of age. and gender on blogging. In AAAI 2006 Spring Symposium on Computational Approaches to Analysing Weblogs, 2006.
12. M. Koppel, S. Argamon and A. R. Shimoni (2003). Automatically Categorizing Written Texts by Author Gender. In Literary and Linguistic Computing, 2003. Mulac, A., L. B. Studley, S. Blau (1990). The gender-linked language effect in primary and secondary students' impromptu essays, Sex Roles 23, 9/10, 1990.
13. Mulac, A., L. B. Studley, S. Blau (1990). The gender-linked language effect in primary and secondary students' impromptu essays, Sex Roles 23, 9/10, 1990.
14. Mulac, A., T. L. Lundell (1994). Effects of gender-linked language differences in adults' written discourse: Multivariate tests of language effects, Language & Communication 14, 3, 1994.
15. Palander-Collin, M. (1999). Male and female styles in 17th century correspondence, Language Variation and Change 11, pp. 123-141.
16. Manber U., Patel A., and Robison J. Experience with Personalization on Yahoo! Communication of the ACM, 43(8): 35-39, 2002.
17. Simkins-Bullock, J. A., B. G. Wildman (1991). An investigation into the relationship between gender and language, Sex Roles 24, 1991.
18. Search Engine Watch Journal, Behavioral Targeting and Contextual Advertising, http://www.searchenginejournal.com/?p=836.
19. Yang, Y., Pedersen J.P. A Comparative Study on Feature Selection in Text Categorization Proceedings of the Fourteenth International Conference on Machine Learning (ICML'97), 1997, pp412-420.
20. Joachims, T. Text Categorization with Support Vector Machines: Learning with Many Relevant Features. In Proceedings of the 10th European Conference on Machine Learning (ECML), Chemnitz, Germany, 137-142, 1998.
21. Vapnik, V.N. The Nature of Statistical Learning Theory. Springer-Verlag, New York, NY, 2000.
22. iMedia Connection: Behavioral Targeting Online Ad Spend, http://www.imediaconnection.com/content/9236.asp
23. G. Golub and C. V. Loan. Matrix Computations, 2nd edition. The Johns Hopkins University Press,Baltimore, Maryland, 1989.
24. B. Sarwar, G. Karypis, J. Konstan, and J. Riedl. Application of dimensionality reduction in recommender systems-a case study, 2000.
25. M. H. Pryor. The effects of singular value decomposition on collaborative filtering. Technical Report PCS-TR98-338, Dartmouth College, Computer Science, Hanover, NH, June 1998.
26. J.H. Lee, "Combining Multiple Evidence from Different Properties of Weighting Schemes," Proceedings of the 18th Annual ACM-SIGIR, pp. 180-188, 1995
27. Pazzani M., Muramatsu J., and Billsus D. Syskill & Webert: Identifying Interesting Web Sites. In Proc. of the 13th National Conference on Artificial Intelligence, pages: 54-61, 1996.
28. S. C. Deerwester, S. T. Dumais, T. K. Landauer, G. W. Furnas, and R. A. Harshman. Indexing by latent semantic analysis. Journal of the American Society of Information Science, 41(6):391-407, 1990.
29. Amanda Lenhart, Susannah Fox. Bloggers: A portrait of the internet's new storytellers, http://www.pewinternet.org/pdfs/ PIP%20Bloggers%20Report%20July%2019%202006.pdf
30. Finn V. Jensen. Bayesian Networks and Decision Graphs. Springer, 2001.
31. M. Berry, T. Do, and S. Varadhan. Svdpackc (version 1.0) user's guide. Technical Report CS-93-194, University of Tennessee, 1993.