Interest-based personalized search

ACM Transactions on Information Systems

Volumn 25, Issue 1, 2007, Pages

  Ma, Zhongming ^a   Pant, Gautam ^a   Sheng, Olivia R Liu ^a  

^a UNIVERSITY OF UTAH   (United States)

Author keywords

Information retrieval; Open Directory; Personalized search; User interest; User interface; World Wide Web

Indexed keywords

LIST INTERFACE SYSTEM (LIST); OPEN DIRECTORY; PERSONALIZED SEARCH; USER INTEREST;

DATA ACQUISITION; INFORMATION RETRIEVAL; SEARCH ENGINES; USER INTERFACES; WEBSITES;

ONLINE SEARCHING;

EID: 33847630874     PISSN: 10468188     EISSN: 15582868     Source Type: Journal    
DOI: 10.1145/1198296.1198301     Document Type: Article

References (54)

1. BRIN, S. AND PAGE, L. 1998. The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Sys. 30, 1-7, 107-117.
2. BRODER, A. 2002. A taxonomy of Web search. ACM SIGIR Forum 36, 2, 3-10.
3. BUDZIK, J. AND HAMMOND, K. 2000. User interactions with everyday applications as context for just-in-time information access. In Proceedings of the 5th International Conference on Intelligent User Interfaces. New Orleans, LA, 44-51.
4. BUTLER, D. 2000. Souped-up search engines. Nature 405, 112-115.
5. CARROLL, J. AND ROSSON, M. B. 1987. The paradox of the active user. In Interfacing Thought-Cognitive Aspects of Human-Computer Interaction, J. M. Carroll, Ed. MIT Press, Cambridge, MA.
6. CHIRITA, P. A., NEJDL, W., PAIU, R., AND KOHLSCHUTTER, C. 2005. Using ODP metadata to personalize search. In. Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development In Information Retrieval. Salvador, Brazil, 178-185.
7. CRASWELL, N., HAWKING, D., AND ROBERTSON, S. 2001. Effective site finding using link information. In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development In Information Retrieval. New Orleans, LA, 250-257.
8. CUTTING, D. R., KARGER, D. R., PEDERSEN, J. O., AND TUKEY, J. W. 1992. Scatter/Gather: A cluster-based approach to browsing large document collections. In Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Copenhagen, Denmark, 318-329.
9. DEERWESTER, S., DUMAIS, S. T., FURNAS, G. W., LANDAUER, T. K., AND HARSHMAN, R. 1990. Indexing by latent semantic analysis. J. Amer. Soc. Inform. Sci. 41, 6, 391-407.
10. DIETTERICH, T. G. 1997. Machine learning research: Four current directions. AI Magazine 18, 4, 97-136.
11. DREILINGER, D. AND HOWE, A. E. 1997. Experiences with selecting search engines using metasearch. ACM. Inform. Sys. 15, 3, 195-222.
12. DUMAIS S. AND CHEN, H. 2001. Optimizing search by showing results in context. In Proceedings of Computer-Human Interaction. Seattle, WA, 277-284.
13. FINKELSTEIN, L., GABRILOVICH, E., MATIAS, Y., RIVLIN, E., SOLAN, Z., WOLFMAN, G., AND RUPPIN, E. 2002. Placing search in context: The concept revisited. ACM Trans. Inform. Syst. 20, 1, 116-131.
14. GAUCH, S., CHAFFEE, J., AND PRETSCHNER, A. 2003. Ontology-based personalized search and browsing. Web Intell. Agent Syst. 1, 3/4, 219-234.
15. GLOVER, E., LAWRENCE, S., BRIMINGHAM, W., AND GILES, C. L. 1999. Architecture of a metasearch engine that supports user information needs. In Proceedings of the 8th International Conference on Information Knowledge Management, Kansas City, MO, 210-216.
16. HAFRI, Y. AND DJERABA, C. 2004. Dominos: A new Web crawler's design. In Proceedings of the 4th International Web Archiving Workshop (IWAW). Beth, UK.
17. HARRIS, Z. 1985. Distributional structure. In The Philosophy of Linguistics. Katz, J. J., Ed. Oxford University Press, Oxford, UK. 26-47.
18. HAVELIWALA, T. H. 2003. Topic-Sensitive PageRank. IEEE Trans. Knowl. Data Engin. 15, 4, 784-796.
19. JANSEN, B. J., SPINK, A., BATEMAN, J., AND SARACEVIC, T. 1998. Real life information retrieval: A study of user queries on the Web. ACM SIGIR Forum 32, 1, 5-17.
20. JANSEN, B. J., SPINK, A., AND SARACEVIC, T. 2000. Real life, real users, and real needs: A study and analysis of user queries on the Web. Inform. Process. Manag. 36, 2, 207-227.
21. JANSEN, B. J., SPINK, A., AND PEDERSON, J. 2005. A temporal comparison of AltaVista Web searching. J. Amer. Soc. Inform. Sci. Techno. 56, 6, 559-570.
22. JANSEN, B. J. AND SPINK, A. 2005. An analysis of Web searching by european AlltheWeb.com users. Inform. Process. Manage. 41, 361-381.
23. JEH, G. AND WIDOM, J. 2003. Scaling personalized Web search. In Proceedings of the 12th International Conference on World Wide Web. Budapest, Hungary, 271-279.
24. KÄKI, M. 2005. Findex: Search result categories help users when document ranking Fails. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. Portland, OR, 131-140.
25. KRAFT, R., MAGHOUL, F., AND CHANG, C. C. 2005. Y!Q: Contextual search at the point of inspiration. In Proceedings of the 14th ACM International Conference on Information and Knowledge Management. Bremen, Germany, 816-823.
26. LAWRENCE, S. 2000. Context in Web search. IEEE Data Engi. Bull. 23, 3, 25-32.
27. LEORY, G., LALLY, A. M., AND CHEN, H. 2003. The use of dynamic contexts to improve casual internet searching. ACM Trans. Inform. Syst. 21, 3, 229-253.
28. LIU, F., YU, C., AND MENG, W. 2004. Personalized Web search for improving retrieval effectiveness. IEEE Trans. Knowl. Data Engin. 16, 1, 28-40.
29. MALTZ, D. AND EHRLICH, K. 1995. Pointing the way: Active collaborative filtering. In Proceedings of the Conference on Computer-Human Interaction. Denver, CO, 202-209.
30. MENCZER, F., PANT, G., AND SRINIVASAN, P. 2004. Topical Web crawlers: Evaluating adaptive algorithms. ACM Trans. Internet Techn. 4, 4, 378-419.
31. MILLER, G., BECKWITH, R., FELLBAUM, C., GROSS, D., AND MILLER, K. 1990. Introduction to WORDNET: An online lexical database. Int. J. Lexico. 3, 4, 235-244.
32. NAJORK, M. AND HEYDON, A. 2001. High-performance Web crawling. In Handbook of Massive Data Sets, J. ABELLO, P. PARDALOS, AND M. RESENDE, Eds. Kluwer Academic Publishers, 25-45.
33. OYAMA, S., KOKUBO, T., AND ISHIDA, T. 2004. Domain-specific Web search with keyword spices. IEEE Trans. Knowl. Data Engin. 16, 1, 17-27.
34. PITKOW, J., SCHUTZE, H., CASS, T., COOLEY, R., TURNBULL, D., EDMONDS, A., ADAR, E., AND BREUEL, T. 2002. Personalized search. Commun. ACM 45, 9, 50-55.
35. PORTER, M. 1980. An Algorithm for suffix stripping. Program 14, 3, 130-137.
36. RILOFF, E. AND SHEPHERD, J. A Corpus-based approach for building semantic lexicons. In Proceedings of the 2nd Conference on Empirical Methods in Natural Language Processing. Providence, RI, 117-124.
37. SALTON, G. AND MCGILL, M. J. 1986. Introduction to Modern Information Retrieval, McGraw-Hill, New York, NY.
38. SEBASTIANI, F. 2002. Machine learning in automated text categorization. ACM Comput. Surv. 34, 1, 1-47.
39. SELLEN, A. J., MURPHY, R., AND SHAW, K. L. 2002. How knowledge workers use the Web. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Changing our World, Changing Ourselves. Minneapolis, MN, 227-234.
40. SHAKES, J., LANGHEINRICH, M., AND ETZIONI, O. 1997. Dynamic reference sifting: A Case study in the homepage domain. In Proceedings of the 6th International World Wide Web Conference. Santa Clara, CA, 189-200.
41. SHEN, D., CHEN, Z., YANG, Q., ZENG, H., ZHANG, B., LU, Y., AND MA, W. 2004. Web-page classification through summarization. In Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Sheffield, South Yorkshire, UK, 242-249.
42. SHEN, X., TAN, B., AND ZHAI, C. X. 2005a. Context-sensitive information retrieval using implicit feedback. In Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Salvador, Brazil, 43-50.
43. SHEN, X., TAN, B., AND ZHAI, C. X. 2005b. Implicit user modeling for personalized search. In Proceedings of the 14th ACM International Conference on Information and Knowledge Management, Bremen, Germany, 824-831.
44. SPERETTA, M. AND GAUCH, S. 2005. Personalizing search based on user search histories. In Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence. Compiegne University of Technology, France, 622-628.
45. SRINIVASAN, P., MENCZER, F., AND PANT, G. 2005. A general evaluation framework for topical crawlers. Inform. Retriev. 8, 3, 417-447.
46. SUGIYAMA, K., HATANO, K., AND YOSHIKAWA, M. 2004. Adaptive Web search based on user profile constructed without any effort from users. In Proceedings of the 13th International Conference on World Wide Web. New York, NY, 675-684.
47. SULLIVAN, D. 2000. NPD Search and portal site study. Search engine watch. http://searchenginewatch.com/sereport/article.php/2162791.
48. TAN, A. H. 2002. Personalized information management for Web intelligence. In Proceedings of World Congress on Computational Intelligence. Honolulu, HI, 1045-1050.
49. TAN, A. H. AND TEO, C. 1998. Learning user profiles for personalized information dissemination. In Proceedings of International Joint Conference on Neural Network, Anchorage, AK, 183-188.
50. TEEVAN, J., DUMAIS, S. T., AND HORVITZ, E. 2005. Personalizing search via automated analysis of interests and activities. In Proceedings of 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Salvador, Brazil, 449-456.
51. WEN, J. R., NIE, J. Y., AND ZHANG, H. J. 2002. Query clustering using user logs. ACM Trans. Inform. Syst. 20, 1, 59-81.
52. XU, J. AND CHOFT W. B. 1996. Query expansion using local and global document analysis. In Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Zurich, Switzerland, 4-11.
53. YANG, Y. AND LIU, X. 1999. A re-examination of text categorization methods. In Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Berkeley, CA, 42-49.
54. ZAMIR, O. AND ETZIONI, O. 1999. Grouper: A dynamic clustering interface to Web search results. Compu. Netw.: Int. J. Comput. Telecomm. Netw. 31, 11-16, 1361-1374.