Abstract
With the exponential growth of the available information on the World Wide Web, a traditional search engine, even if based on sophisticated document indexing algorithms, has difficulty meeting efficiency and effectiveness performance demanded by users searching for relevant information. Users surfing the Web in search of resources to satisfy their information needs have less and less time and patience to formulate queries, wait for the results and sift through them. Consequently, it is vital in many applications - for example in an e-commerce Web site or in a scientific one - for the search system to find the right information very quickly. Personalized Web environments that build models of short-term and long-term user needs based on user actions, browsed documents or past queries are playing an increasingly crucial role: they form a winning combination, able to satisfy the user better than unpersonalized search engines based on traditional Information Retrieval (IR) techniques. Several important user personalization approaches and techniques developed for the Web search domain are illustrated in this chapter, along with examples of real systems currently being used on the Internet.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Adomavicius, G., Tuzhilin, A.: User profiling in personalization applications through rule discovery and validation. In: KDD ’99: Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 377–381. ACM Press, New York (1999)
Aktas, M.S., Nacar, M.A., Menczer, F.: Personalizing PageRank Based on Domain Profiles. In: Mobasher, B., Nasraoui, O., Liu, B., Masand, B. (eds.) WebKDD 2004. LNCS (LNAI), vol. 3932, pp. 83–90. Springer, Heidelberg (2006)
Allan, J.: Incremental relevance feedback for information filtering. In: Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Zurich, Switzerland, pp. 270–278. ACM Press, New York (1996)
Almeida, R.B., Almeida, V.A.F.: A community-aware search engine. In: Proceedings of the 13th international conference on World Wide Web, WWW ’04, pp. 413–421. ACM Press, New York (2004)
Anick, P.: Using terminological feedback for web search refinement: a log-based study. In: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval. SIGIR ’03, pp. 88–95. ACM Press, New York (2003)
Asnicar, F.A., Tasso, C.: ifWeb: a prototype of user model-based intelligent agent for document filtering and navigation in the world wide web. In: Proceedings of Workshop Adaptive Systems and User Modeling on the World Wide Web (UM97), Sardinia, Italy, pp. 3–12 (1997)
Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley, Reading (1999), http://sunsite.dcc.uchile.cl/irbook
Bharat, K., Kamba, T., Albers, M.: Personalized, interactive news on the Web. Multimedia Syst. 6(5), 349–358 (1998)
Budzik, J., Hammond, K.J.: User interactions with everyday applications as context for just-in-time information access. In: IUI ’00: Proceedings of the 5th international conference on Intelligent user interfaces, pp. 44–51. ACM Press, New York (2000)
Budzik, J., Hammond, K.J., Birnbaum, L.: Information access in context. Knowledge-Based Systems 14(1-2), 37–53 (2001)
Bunt, A., Carenini, G., Conati, C.: Adaptive content presentation for the Web. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 409–432. Springer, Heidelberg (2007)
Burke, R.: Hybrid Web Recommender Systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 377–408. Springer, Heidelberg (2007)
Chan, P.K.: Constructing Web User Profiles: A non-invasive Learning Approach. In: Masand, B., Spiliopoulou, M. (eds.) Web Usage Analysis and User Profiling. LNCS (LNAI), vol. 1836, pp. 39–55. Springer, Heidelberg (2000)
Chang, H., Cohn, D., McCallum, A.: Learning to Create Customized Authority Lists. In: Proceedings of the Seventeenth International Conference on Machine Learning. ICML ’00, pp. 127–134. Morgan Kaufmann Publishers Inc., San Francisco (2000)
Chirita, P.-A., Olmedilla, D., Nejdl, W.: PROS: A Personalized Ranking Platform for Web Search. In: De Bra, P., Nejdl, W. (eds.) AH 2004. LNCS, vol. 3137, pp. 34–43. Springer, Heidelberg (2004)
Claypool, M., Gokhale, A., Miranda, T., Murnikov, P., Netes, D., Sartin, M.: Combining content-based and collaborative filters in an online newspaper. In: ACM SIGIR Workshop on Recommender Systems - Implementation and Evaluation, ACM Press, New York (1999), http://www.csee.umbc.edu/~ian/sigir99-rec/
Claypool, M., Le, P., Wased, M., Brown, D.: Implicit interest indicators. In: Proceedings of the 6th international conference on Intelligent user interfaces. IUI ’01, pp. 33–40. ACM Press, New York (2001)
Collins, A.M., Quillian, R.M.: Retrieval time from semantic memory. Journal of Learning and Verbal Behavior 8, 240–247 (1969)
Cutting, D.R., Karger, D.R., Pedersen, J.O., Tukey, J.W.: Scatter/Gather: a cluster-based approach to browsing large document collections. In: SIGIR ’92: Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 318–329. ACM Press, New York (1992)
Deerwester, S.C., Dumais, S.T., Landauer, T.K., Furnas, G.W., Harshman, R.A.: Indexing by Latent Semantic Analysis. Journal of the American Society of Information Science 41(6), 391–407 (1990)
Dieberger, A., Dourish, P., Höök, K., Resnick, P., Wexelblat, A.: Social navigation: techniques for building more usable systems. Interactions 7(6), 36–45 (2000)
Dolog, P., Henze, N., Nejdl, W., Sintek, M.: Towards the Adaptive Semantic Web. In: Bry, F., Henze, N., Małuszyński, J. (eds.) PPSWR 2003. LNCS, vol. 2901, pp. 51–68. Springer, Heidelberg (2003)
Dolog, P., Nejdl, W.: Semantic Web Technologies for Personalized Information Access on the Web. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 697–719. Springer, Heidelberg (2007)
Dumais, S., Cutrell, E., Cadiz, J., Jancke, G., Sarin, R., Robbins, D.C.: Stuff I’ve seen: a system for personal information retrieval and re-use. In: SIGIR ’03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pp. 72–79. ACM Press, New York (2003)
Ferragina, P., Gulli, A.: A personalized search engine based on web-snippet hierarchical clustering. In: WWW ’05: Special interest tracks and posters of the 14th international conference on World Wide Web, pp. 801–810. ACM Press, New York (2005)
Freyne, J., Smyth, B.: An Experiment in Social Search. In: De Bra, P., Nejdl, W. (eds.) AH 2004. LNCS, vol. 3137, pp. 95–103. Springer, Heidelberg (2004)
Furnas, G.W., Landauer, T.K., Gomez, L.M., Dumais, S.T.: The vocabulary problem in human-system communication. Commun. ACM 30(11), 964–971 (1987)
Gauch, S., Chaffee, J., Pretschner, A.: Ontology-based personalized search and browsing. Web Intelligence and Agent System 1(3-4), 219–234 (2003)
Gauch, S., Speretta, M., Chandramouli, A., Micarelli, A.: User profiles for personalized information access. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 54–89. Springer-Verlag, Berlin Heidelberg New York (2007)
Gentili, G., Micarelli, A., Sciarrone, F.: Infoweb: An Adaptive Information Filtering System for the Cultural Heritage Domain. Applied Artificial Intelligence 17(8-9), 715–744 (2003)
Glance, N.S.: Community search assistant. In: IUI ’01: Proceedings of the 6th international conference on Intelligent user interfaces, pp. 91–96. ACM Press, New York (2001)
Goldberg, D., Nichols, D., Oki, B.M., Terry, D.: Using collaborative filtering to weave an information tapestry. Commun. ACM 35(12), 61–70 (1992)
Golub, G.H., van Loan, C.F.: Matrix computations, 3rd edn. Johns Hopkins University Press, Baltimore (1996)
Haveliwala, T.H.: Topic-sensitive PageRank. In: WWW ’02: Proceedings of the 11th international conference on World Wide Web, pp. 517–526. ACM Press, New York (2002)
Höscher, C., Strube, G.: Web Search Behavior of Internet Experts and Newbies. In: Proceedings of the 9th World Wide Web Conference, WWW9, Amsterdam, Netherlands, pp. 337–346 (2000)
Jameson, A., Smyth, B.: Recommending to Groups. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 596–627. Springer, Heidelberg (2007)
Jeh, G., Widom, J.: Scaling personalized web search. In: WWW ’03: Proceedings of the 12th international conference on World Wide Web, pp. 271–279. ACM Press, New York (2003)
Joachims, T.: Optimizing search engines using clickthrough data. In: Proceedings of 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 133–142. ACM Press, New York (2002)
John Kemeny, J.L.S.: Mathematical Models in the Social Sciences. MIT Press, New York (1962)
Kelly, D., Teevan, J.: Implicit feedback for inferring user preference: a bibliography. SIGIR Forum 37(2), 18–28 (2003)
Khopkar, Y., Spink, A., Giles, C.L., Shah, P., Debnath, S.: Search engine personalization: An exploratory study. First Monday 8(7) (2003), http://www.firstmonday.org/issues/issue8_7/khopkar/index.html
Kleinberg, J.: Authoritative Sources in a Hyperlinked Environment. In: Proceedings of the 9th annual ACM-SIAM symposium on Discrete algorithms, San Francisco, USA, pp. 668–677. ACM Press, New York (1998)
Kobsa, A.: Privacy-Enhanced Web Personalization. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 628–670. Springer, Heidelberg (2007)
Koenemann, J., Belkin, N.J.: A case for interaction: a study of interactive information retrieval behavior and effectiveness. In: CHI ’96: Proceedings of the SIGCHI conference on Human factors in computing systems, pp. 205–212. ACM Press, New York (1996)
Koutrika, G., Ioannidis, Y.: A Unified User Profile Framework for Query Disambiguation and Personalization. In: Proceedings of the Workshop on New Technologies for Personalized Information Access (PIA2005), Edinburgh, Scotland, UK, pp. 44–53 (2005), http://irgroup.cs.uni-magdeburg.de/pia2005/docs/KouIoa05.pdf
Kritikopoulos, A., Sideri, M.: The Compass Filter: Search Engine Result Personalization Using Web Communities. In: Mobasher, B., Anand, S.S. (eds.) ITWP 2003. LNCS (LNAI), vol. 3169, pp. 229–240. Springer, Heidelberg (2005)
Kulyukin, V.A.: Application-Embedded Retrieval from Distributed Free-Text Collections. In: AAAI/IAAI, pp. 447–452 (1999)
de Lathauwer, L., de Moor, B., Vandewalle, J.: A Multilinear Singular Value Decomposition. SIAM J. Matrix Anal. Appl. 21(4), 1253–1278 (2000)
Lawrence, S.: Context in Web Search. IEEE Data Eng. Bull. 23(3), 25–32 (2000)
Lawrence, S., Giles, C.L.: Context and Page Analysis for Improved Web Search. IEEE Internet Computing 2(4), 38–46 (1998)
Liu, F., Yu, C., Meng, W.: Personalized Web Search For Improving Retrieval Effectiveness. IEEE Transactions on Knowledge and Data Engineering 16(1), 28–40 (2004)
MacQueen, J.B.: Some methods for classification and analysis of multivariate observations. In: Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297. University of California Press (1967)
Micarelli, A., Gasparetti, F.: Adaptive Focused Crawling. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 231–262. Springer, Heidelberg (2007)
Micarelli, A., Sciarrone, F.: Anatomy and Empirical Evaluation of an Adaptive Web-Based Information Filtering System. User Modeling and User-Adapted Interaction 14(2-3), 159–200 (2004)
Micarelli, A., Sciarrone, F., Marinilli, M.: Web Document modeling. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 155–194. Springer, Heidelberg (2007)
Middleton, S.E., De Roure, D.C., Shadbolt, N.R.: Capturing knowledge of user preferences: ontologies in recommender systems. In: K-CAP ’01: Proceedings of the 1st international conference on Knowledge capture, pp. 100–107. ACM Press, New York (2001)
Mobasher, B.: Data Mining for Web Personalization. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 90–135. Springer, Heidelberg (2007)
Montaner, M., Lopez, B., De La Rosa, J.L.: A Taxonomy of Recommender Agents on the Internet. Artificial Intelligence Review 19, 285–330 (2003)
Oard, D.W.: The state of the art in text filtering. User Modeling and User-Adapted Interaction 7(3), 141–178 (1997)
Olston, C., Chi, E.H.: ScentTrails: Integrating Browsing and Searching on the Web. ACM Transactions on Computer-Human Interaction 10(3), 177–197 (2003)
Pirolli, P.L.T., Pitkow, J.E.: Distributions of surfers’ paths through the World Wide Web: Empirical characterizations. World Wide Web 2(1-2), 29–45 (1999)
Pitkow, J., Schütze, H., Cass, T., Cooley, R., Turnbull, D., Edmonds, A., Adar, E., Breuel, T.: Personalized search. Commun. ACM 45(9), 50–55 (2002)
Qiu, F., Cho, J.: Automatic identification of user interest for personalized search. In: WWW ’06: Proceedings of the 15th international conference on World Wide Web, pp. 727–736. ACM Press, New York (2006)
Quillian, R.M.: Semantic memory. In: Minsky, M. (ed.) Semantic information processing, pp. 216–270. MIT Press, Cambridge (1968), http://citeseer.ist.psu.edu/ambrosini97hybrid.html
Raghavan, V.V., Sever, H.: On the Reuse of Past Optimal Queries. In: Research and Development in Information Retrieval, pp. 344–350 (1995), http://citeseer.ist.psu.edu/raghavan95reuse.html
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: an open architecture for collaborative filtering of netnews. In: CSCW ’94: Proceedings of the 1994 ACM conference on Computer supported cooperative work, pp. 175–186. ACM Press, New York (1994)
Resnick, P., Varian, H.R.: Recommender systems. Commun. ACM 40(3), 56–58 (1997)
Rhodes, B.J.: Just-In-Time Information Retrieval. PhD thesis, MIT Media Laboratory, Cambridge, MA (May 2000), http://citeseer.ist.psu.edu/rhodes00justtime.html
Rich, E.: User modeling via stereotypes. In: Readings in intelligent user interfaces, pp. 329–342. Morgan Kaufmann Publishers Inc., San Francisco (1998)
Van Rijsbergen, C.J.: Information Retrieval. Butterworth-Heinemann, Newton (1979)
Robertson, S.E.: Theories and Models in Information Retrieval. Journal of Documentation 33(2), 126–148 (1977)
Salton, G., McGill, M.: An Introduction to modern information retrieval. Mc-Graw-Hill, New York (1983)
Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Commun. ACM 18(11), 613–620 (1975)
Savoy, J., Picard, J.: Retrieval Effectiveness on the Web. Information Processing & Management 37(4), 543–569 (2001)
Schafer, J.B., Frankowski, D., Herlocker, J.L., Sen, S.: Collaborative Filtering Recommender Systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization. LNCS, vol. 4321, pp. 291–324. Springer, Heidelberg (2007)
Smyth, B., Balfe, E., Freyne, J., Briggs, P., Coyle, M., Boydell, O.: Exploiting query repetition and regularity in an adaptive community-based web search engine. User Modeling and User-Adapted Interaction 14(5), 383–423 (2005)
Speretta, M., Gauch, S.: Personalized Search Based on User Search Histories. In: Web Intelligence (WI2005), France, pp. 622–628. IEEE Computer Society Press, Los Alamitos (2005), http://dx.doi.org/10.1109/WI.2005.114
Spink, A., Jansen, B.J.: A study of Web search trends. Webology 1(2), 4 (2004), http://www.webology.ir/2004/v1n2/a4.html
Spink, A., Jansen, B.J., Ozmultu, H.C.: Use of query reformulation and relevance feedback by Excite users. Internet Research: Electronic Networking Applications and Policy 10(4), 317–328 (2000), http://citeseer.ist.psu.edu/spink00use.html
Sun, J.-T., Zeng, H.-J., Liu, H., Lu, Y., Chen, Z.: CubeSVD: a novel approach to personalized Web search. In: WWW ’05: Proceedings of the 14th international conference on World Wide Web, pp. 382–390. ACM Press, New York (2005)
Tanudjaja, F., Mui, L.: Persona: A Contextualized and Personalized Web Search. In: HICSS ’02: Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS’02), vol. 3, Washington, DC, USA, p. 67. IEEE Computer Society Press, Los Alamitos (2002)
Tasso, C., Omero, P.: La Personalizzazione dei contenuti Web: e-commerce, i-access, e-government. Franco Angeli (2002)
Teevan, J.: Seesaw: Personalized web search. Student Workshop for Information Retrieval and Language, SWIRL ’04 (November 2004), http://ciir.cs.umass.edu/~hema/swirl/swirl.htm
Teevan, J., Alvarado, C., Ackerman, M.S., Karger, D.R.: The perfect search engine is not enough: a study of orienteering behavior in directed search. In: CHI ’04: Proceedings of the SIGCHI conference on Human factors in computing systems, New York, pp. 415–422. ACM Press, New York (2004)
Teevan, J., Dumais, S.T., Horvitz, E.: Personalizing search via automated analysis of interests and activities. In: SIGIR ’05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval, New York, pp. 449–456. ACM Press, New York (2005)
Wærn, A.: User Involvement in Automatic Filtering: An Experimental Study. User Modeling and User-Adapted Interaction 14(2-3), 201–237 (2004)
Webb, G.I., Pazzani, M., Billsus, D.: Machine Learning for User modeling. User Modeling and User-Adapted Interaction 11(1-2), 19–29 (2001)
White, R., Jose, J.M., Ruthven, I.: Comparing explicit and implicit feedback techniques for web retrieval: Trec-10 interactive track report. In: TREC (2001) http://trec.nist.gov/pubs/trec10/papers/glasgow.pdf
Ahn, J.-w., Brusilovsky, P., Farzan, R.: Investigating Users Needs and Behavior for Social Search. In: Ardissono, L., Brna, P., Mitrović, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 1–12. Springer, Heidelberg (2005) http://irgroup.cs.uni-magdeburg.de/pia2005/docs/AhnBruFar05.pdf
Yao, Y.Y.: Measuring Retrieval Effectiveness based on User Preference of Documents. Journal of the American Society for Information Science 46(2), 133–145 (1995)
Zamir, O., Etzioni, O.: Web document clustering: a feasibility demonstration. In: SIGIR ’98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval, pp. 46–54. ACM Press, New York (1998)
Zamir, O.E., Korn, J.L., Fikes, A.B., Lawrence, S.R.: Us patent application #0050240580: Personalization of placed content ordering in search results (July 2004)
Zeng, H.-J., He, Q.-C., Chen, Z., Ma, W.-Y., Ma, J.: Learning to cluster web search results. In: SIGIR ’04: Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 210–217. ACM Press, New York (2004)
Zhao, Q., Hoi, S.C.H., Liu, T.-Y., Bhowmick, S.S., Lyu, M.R., Ma, W.-Y.: Time-dependent semantic similarity measure of queries using historical click-through data. In: WWW ’06: Proceedings of the 15th international conference on World Wide Web, pp. 543–552. ACM Press, New York (2006)
Zukerman, I., Albrecht, D.W.: Predictive Statistical Models for User Modeling. User Modeling and User-Adapted Interaction 11(1-2), 5–18 (2001)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this chapter
Cite this chapter
Micarelli, A., Gasparetti, F., Sciarrone, F., Gauch, S. (2007). Personalized Search on the World Wide Web. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds) The Adaptive Web. Lecture Notes in Computer Science, vol 4321. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72079-9_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-72079-9_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72078-2
Online ISBN: 978-3-540-72079-9
eBook Packages: Computer ScienceComputer Science (R0)