A method for managing access to web pages: Filtering by Statistical Classification (FSC) applied to text

Decision Support Systems

Volumn 42, Issue 1, 2006, Pages 144-161

  Caulkins, Jonathan P ^a   Ding, Wenxuan ^b   Duncan, George ^a   Krishnan, Ramayya ^a   Nyberg, Eric ^c  

^a CARNEGIE MELLON UNIVERSITY   (United States)

^b 1120 Science and Engineering Offices   (United States)

^c Carnegie Mellon University   (United States)

Author keywords

Content based filtering; Decision support; Statistical classification techniques

Indexed keywords

DATA STRUCTURES; ELECTRIC FILTERS; MATHEMATICAL MODELS; STATISTICAL METHODS; TEXT PROCESSING; USER INTERFACES; WEBSITES;

CONTENT-BASED FILTERING; DECISION SUPPORT; FILTERING BY STATISTICAL CLASSIFICATION (FSC); STATISTICAL CLASSIFICATION TECHNIQUES;

CLASSIFICATION (OF INFORMATION);

EID: 33747786298     PISSN: 01679236     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dss.2004.11.015     Document Type: Article

References (47)

1. Akaike H. Information theory and an extension of the maximum likelihood principle. In: Petrov B., and Csake F. (Eds). Second international symposium on information theory (1973), Akadémiai Kiado, Budapest
2. Balabanovic M., and Shoham Y. Fab: content-based, collaborative recommendation. Communications of the ACM 97 3 (1997) 66-72
3. Boley D., Gini M., Gross R., Han E.-H., Hastings K., Karypis G., Kumar V., Mobasher B., and Moore J. Partitioning-based clustering for web document categorization. Decision Support Systems 27 (1999) 329-341
4. Boone G. Concept features in Re: agent, an intelligent email agent. Proceedings of the second International Conference on Autonomous Agents, Minneapolis (1998)
5. Center Jr. J.L. Bayesian classification using an entropy prior on mixture models. Proceedings 19th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (1999) 42-70
6. Cheeseman P., and Stutz J. Bayesian classification (AutoClass): theory and results. In: Fayyad U.M., PiatetskyShapiro G., Smyth P., and Uthurusamy R. (Eds). Advances in knowledge discovery and data mining (1996), AAAI Press, Menlo Park, CA 158-180
7. L.F. Cranor, P. Resnick, D. Gallo, Technology inventory: a catalog of tools that support parents' ability to choose online content appropriate for their children. Prepared for the Internet Online Summit: Focus on Children, December 1997, revised September, 1998 for America Links Up. http://www.research.att.com/projects/tech4kids/.
8. M. Craven, D. Freitag, A. McCallum, T. Mitchell, K. Nigam, C.Y. Quek, Learning to extract symbolic knowledge from the world wide web. Technical Report, Carnegie Mellon University, 1997.
9. De Loupy C., Bellot P., El-Beze M., and Marteau P.F. Query expansion and classification of retrieved documents. Seventh text retrieval conference (TREC-7) (1998) 443-450
10. Desu M.M., and Raghavarao D. Sample size methodology (1990), Academic Press, Boston
11. W. Ding, Implementing parental control on access to inappropriate web pages: Filtering by a Good word/Bad word Probit analysis, Master of Philosophy thesis, Carnagie Mellon University, 2000.
12. Dumais S.T. Latent semantic indexing and TREC-2. In: Harman D. (Ed). The second text retrieval conference (TREC2) (1994) 105-116
13. Gibbons A. Algorithmic graph theory (1985), Cambridge University Press
14. Greene W.H. Econometric analysis. Third edition (1997), Prentice-Hall 882-885
15. Hagerup T., and Rub C. A guided tour of chernoff bounds. Information Processing Letters 33 (1989) 305-308
16. Hartigan J.A., and Wong M.A. A K-means clustering algorithm: algorithm AS 136. Applied Statistics 28 (1979) 126-130
17. Herlocker J., Konstan J., and Riedl J. Explaining collaborative filtering recommendations. Proceedings of ACM 2000 Conference on Computer Supported Cooperative Work (2000) 241-250
18. Heuser U., and Rosenstiel W. Automatic generation of local Internet catalogues using hierarchical radius-based competitive learning. Proceedings 14th European Conference on Artificial Intelligence (2000) 306-310
19. Jacob V., Krishnan R., Ryu Y.U., Chandrasekaran R., and Hong S. Filtering objectionable internet content. Proceedings of the 20th International Conference on Information Systems (1999)
20. Jain K., and Dubes R.C. Algorithms for clustering data (1988), Prentice Hall, Englewood Cliffs, NJ
21. Joseph L., and Belisle P. Bayesian sample size determination for normal means and differences between normal means. The Statistician 46 2 (1997) 209-226
22. Landauer T.K., Foltz P.W., and Laham D. An introduction to latent semantic analysis. Discourse Processes 25 (1998) 259-284
23. Lashkari Y., Metral M., and Maes P. Collaborative interface agents. Proceedings of the Twelfth National Conference on Artificial Intelligence, Seattle (1994), AAAI Press 444-450
24. Lasica J. Ratings today, censorship tomorrow. Salon Magazine (1997 (July))
25. Lee P.Y., Hui S.C., and Fong A.C.M. Neural network for web content filtering. IEEE Intelligent Systems 17 5 (2002) 48-57
26. Lieberman H. Letizia: an agent that assists web browsing. Proceedings of the International Joint Conference on Artificial Intelligence, Montreal (1995)
27. Maes P., and Kozierok R. Learning interface agent. Proceedings of Eleventh National Conference on Artificial Intelligence (1993), MIT Press
28. Menhaj M.B., and Delgosha F. A soft probabilistic neural network for implementation of Bayesian classifiers. Proceedings International Joint Conference on Neural Networks (2001) 454-458
29. Midine D., Spiegelhalter D.J., and Taylor C.C. Machine learning, neural and statistical classification (1994), Ellis Horwood, New York edited collection
30. J. Miller, P. Resnick, D. Singer, Rating service and rating systems (and their machine readable descriptions), http://w3.org/PICS/services.html, May, World Wide Web Consortium, 1996.
31. R.A. Mollineda, E. Vidal, A relative approach to hierarchical clustering, pattern recognition and applications (frontiers in artificial intelligence and applications Vol.56) p. viii+287, 19-28, 2000.
32. Morita M., and Shinoda Y. Information filtering based on user behavior analysis and best match text retrieval. Proceedings of the 17th ACM Annual International Conference on Research and Development in Information Retrieval (SIGIR'94) (1994), Springer-Verlag, Dublin, Ireland 272-281
33. Pazzani M.J., Muramatsu J., and Billus D. Syskill & Webert: identifying interesting web sites. Proceedings of Thirteenth National Conference on Artificial Intelligence, Portland (1996), AAAI Press 54-61
34. Quinlan J.R. C4.5: programs for machine learning (1993), Morgan Kaufmann Publishers, San Mateo, CA
35. Rashid A.M., Albert I., Cosley D., Lam S.K., McNee S., Konstan J.A., and Riedl J. Getting to know you: learning new user preferences in recommender systems. Proceedings of the 2002 International Conference on Intelligent User Interfaces, San Francisco, CA (2002) 127-134
36. Resnick P. Filtering information on the Internet (1997 (March)), Scientific American
37. Resnick P., and Miller J. PICS: internet access controls without censorship. Communications of the ACM (1996 (October)) 87-93
38. Salton G., and McGill M.J. Introduction to modern information retrieval (1993), McGraw-Hill, New York
39. Sarkar S., and Sriram R. Bayesian models for early warning of bank failures. Management Science 47 11 (2001) 1457-1475
40. Shapira B., Shoval P., and Hanani U. Experimentation with an information filtering system that combines cognitive and sociological filtering integrated with user stereotypes. Decision Support Systems 27 (1999) 5-24
41. Sheth B., and Maes P. Evolving agents for personalized information filtering. Proceedings of the Ninth IEEE Conference on Artificial Intelligence for Applications (1993)
42. Sierra B., Serrano N., Larranaga P., Plasencia E.J., Inza I., Jimenez J.J., Revuelta P., and Mora M.L. Using Bayesian networks in the construction of a bi-level multi-classifier: a case study using intensive care unit patients' data. Artificial Intelligence in Medicine 22 3 (2001) 233-248
43. Survey, National Public Radio, the Kaiser Family Foundation, and Harvard's Kennedy School of Government, http://www.npr.org/programs/specials/poll/technology, 2000.
44. Tanner M.A. Tools for statistical inference (1996), Springer-Verlag
45. Wang Z., Li J., Wiederhold G., and Firschein O. Classifying objectionable websites based on image content. IDMS (1998) 113-124
46. J. Weinberg, Rating the net. http://www.msen.com/~weinberg/rating.htm, 1997.
47. Wulfekuhler M.R., and Punch W.F. Finding salient features for personal web page categories. Proc. of 6th International World Wide Web Conference (1997 (April)). http://www.scope.gmd.de/info/www6/technical/paper118/paper118.html http://www.scope.gmd.de/info/www6/technical/paper118/paper118.html.