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Intelligent Search on the Internet

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Reasoning, Action and Interaction in AI Theories and Systems

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4155))

Abstract

The Web has grown from a simple hypertext system for research labs to an ubiquitous information system including virtually all human knowledge, e.g., movies, images, music, documents, etc. The traditional browsing activity seems to be often inadequate to locate information satisfying the user needs. Even search engines, based on the Information Retrieval approach, with their huge indexes show many drawbacks, which force users to sift through long lists of results or reformulate queries several times. Recently, an important research activity effort has been focusing on this vast amount of machine-accessible knowledge and on how it can be exploited in order to match the user needs. The personalization and adaptation of the human-computer interaction in information seeking by means of machine learning techniques and in AI-based representations of the information help users to address the overload problem. This chapter illustrates the most important approaches proposed to personalize the access to information, in terms of gathering resources related to given topics of interest and ranking them as a function of the current user needs and activities, as well as examples of prototypes and Web systems.

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References

  1. Aggarwal, C.C., Al-Garawi, F., Yu, P.S.: Intelligent crawling on the world wide web with arbitrary predicates. In: Proceedings of the 10th World Wide Web Conference (WWW 10), Hong Kong, pp. 96–105 (2001)

    Google Scholar 

  2. Ambrosini, L., Cirillo, V., Micarelli, A.: A hybrid architecture for user-adapted information filtering on the world wide web. In: Jameson, A., Paris, C., Tasso, C. (eds.) Proceedings of the 6th International Conference on User Modeling (UM 1997), pp. 59–61. Springer, Berlin (1997)

    Google Scholar 

  3. 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 (UM 1997), Sardinia, Italy, pp. 3–12 (1997)

    Google Scholar 

  4. Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley, Reading (1999)

    Google Scholar 

  5. Balabanović, M., Shoham, Y.: Fab: content-based, collaborative recommendation. Communications of the ACM 40(3), 66–72 (1997)

    Article  Google Scholar 

  6. Bharat, K., Kamba, T., Albers, M.: Personalized, interactive news on the web. Multimedia Syst. 6(5), 349–358 (1998)

    Article  Google Scholar 

  7. Bonabeau, E., Dorigo, M., Theraulaz, G.: Inspiration for optimization from social insect behavior. Nature 406, 39–42 (2000)

    Article  Google Scholar 

  8. Boone, G.: Concept features in re:agent, an intelligent email agent. In: Proceedings of the second international conference on Autonomous agents (AGENTS 1998), pp. 141–148. ACM Press, New York (1998)

    Chapter  Google Scholar 

  9. Buckley, C., Salton, G., Allan, J.: The effect of adding relevance information in a relevance feedback environment. In: SIGIR 1994: Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 292–300. Springer, New York (1994)

    Google Scholar 

  10. Carberry, S.: Techniques for plan recognition. User Modeling and User-Adapted Interaction 11(1-2), 31–48 (2001)

    Article  MATH  Google Scholar 

  11. Chakrabarti, S., Punera, K., Subramanyam, M.: Accelerated focused crawling through online relevance feedback. In: WWW 2002: Proceedings of the 11th international conference on World Wide Web, pp. 148–159. ACM Press, New York (2002)

    Chapter  Google Scholar 

  12. Chakrabarti, S., van den Berg, M., Dom, B.: Focused crawling: A new approach to topic-specific web resource discovery. In: Proceedings of the 8th World Wide Web Conference (WWW 8), Toronto, Canada, pp. 1623–1640 (1999)

    Google Scholar 

  13. Cooper, W.S.: A definition of relevance for information retrieval. Information Storage and Retrieval 7, 19–37 (1971)

    Article  Google Scholar 

  14. Davison, B.D.: Topical locality in the web. In: SIGIR 2000: Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval, pp. 272–279. ACM Press, New York (2000)

    Chapter  Google Scholar 

  15. 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)

    Article  Google Scholar 

  16. 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)

    Chapter  Google Scholar 

  17. Doorenbos, R.B., Etzioni, O., Weld, D.S.: A scalable comparison-shopping agent for the world-wide web. In: AGENTS 1997: Proceedings of the first international conference on Autonomous agents, pp. 39–48. ACM Press, New York (1997)

    Chapter  Google Scholar 

  18. Frasconi, P., Soda, G., Vullo, A.: Text categorization for multi-page documents: A hybrid naive bayes HMM approach. In: ACM/IEEE Joint Conference on Digital Libraries, JCDL 2001, Roanoke, VA, USA. ACM, New York (2001)

    Google Scholar 

  19. Fung, R., Del Favero, B.: Applying Bayesian networks to information retrieval. Communications of the ACM 38(3), 42–48 (1995)

    Article  Google Scholar 

  20. Gasparetti, F., Micarelli, A.: Adaptive web search based on a colony of cooperative distributed agents. In: Klusch, M., Omicini, A., Ossowski, S., Laamanen, H. (eds.) CIA 2003. LNCS, vol. 2782, pp. 168–183. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  21. Gasparetti, F., Micarelli, A.: Swarm intelligence: Agents for adaptive web search. In: Proceedings of the 16th European Conference on Artificial Intelligence, ECAI 2004 (2004)

    Google Scholar 

  22. Gentili, G., Marinilli, M., Micarelli, A., Sciarrone, F.: Text categorization in an intelligent agent for filtering information on the web. IJPRAI 15(3), 527–549 (2001)

    Google Scholar 

  23. Gulli, A., Signorini, A.: The indexable web is more than 11.5 billion pages. In: WWW 2005: Special interest tracks and posters of the 14th international conference on World Wide Web, pp. 902–903. ACM Press, New York (2005)

    Chapter  Google Scholar 

  24. Joachims, T., Freitag, D., Mitchell, T.M.: Webwatcher: A tour guide for the world wide web. In: Proceedings of the 15h International Conference on Artificial Intelligence (IJCAI 1997), pp. 770–777 (1997)

    Google Scholar 

  25. Kelly, D., Teevan, J.: Implicit feedback for inferring user preference: a bibliography. SIGIR Forum 37(2), 18–28 (2003)

    Article  Google Scholar 

  26. Kruger, A., Giles, C.L., Coetzee, F.M., Glover, E., Flake, G.W., Lawrence, S., Omlin, C.: Deadliner: building a new niche search engine. In: CIKM 2000: Proceedings of the ninth international conference on Information and knowledge management, pp. 272–281. ACM Press, New York (2000)

    Chapter  Google Scholar 

  27. Krulwich, B., Burkey, C.: The contactfinder agent: Answering bulletin board questions with referrals. In: Proceedings of the 13th National Conference on Artificial Intelligence and 8th Innovative Applications of Artificial Intelligence Conference, AAAI 1996, pp. 10–15 (1996)

    Google Scholar 

  28. Lan, M., Tan, C.-L., Low, H.-B., Sung, S.-Y.: A comprehensive comparative study on term weighting schemes for text categorization with support vector machines. In: WWW 2005: Special interest tracks and posters of the 14th international conference on World Wide Web, pp. 1032–1033. ACM Press, New York (2005)

    Chapter  Google Scholar 

  29. Levy, A.Y., Weld, D.S.: Intelligent internet systems. Artificial Intelligence 118(1-2), 1–14 (2000)

    Article  Google Scholar 

  30. Lieberman, H.: Letizia: An agent that assists web browsing. In: Mellish, C.S. (ed.) Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI 1995), Montreal, Quebec, Canada, pp. 924–929. Morgan Kaufmann publishers Inc., San Mateo (1995)

    Google Scholar 

  31. Lieberman, H., Van Dyke, N.W., Vivacqua, A.S.: Let’s browse: A collaborative web browsing agent. In: Proceedings of the 4th International Conference on Intelligent User Interfaces (IUI 1999), Los Angeles, CA, USA, pp. 65–68. ACM Press, New York (1998)

    Google Scholar 

  32. 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)

    Article  Google Scholar 

  33. Magnini, B., Strapparava: User modelling for news web sites with word sense based techniques. User Modeling and User-Adapted Interaction 14(2), 239–257 (2004)

    Article  Google Scholar 

  34. McCallum, A., Nigam, K.: A comparison of event models for naive bayes text classification. In: Proceedings of AAAI 1998, Workshop on Learning for Text Categorization (1998)

    Google Scholar 

  35. Menczer, F., Belew, R.K.: Adaptive retrieval agents: Internalizing local context and scaling up to the web. Machine Learning 31(11-16), 1653–1665 (2000)

    Google Scholar 

  36. 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)

    Article  Google Scholar 

  37. Miller, G.A., Fellbaum, C.: Lexical and conceptual semantics. In: Levin, B., Pinker, S. (eds.) Advances in Neural Information Processing Systems, pp. 197–229. Blackwell, Cambridge (1993)

    Google Scholar 

  38. Minsky, M.: A framework for representing knowledge. Technical report, Massachusetts Institute of Technology, Cambridge, MA, USA (1974)

    Google Scholar 

  39. Mizuuchi, Y., Tajima, K.: Finding context paths for web pages. In: Proceedings of the 10th ACM Conference on Hypertext and Hypermedia: Returning to Our Diverse Roots (HYPERTEXT 1999), Darmstadt, Germany, pp. 13–22 (1999)

    Google Scholar 

  40. Moukas, A., Maes, P.: Amalthaea: An evolving multi-agent information filtering and discovery system for the WWW. Autonomous Agents and Multi-Agent Systems 1(1), 59–88 (1998)

    Article  Google Scholar 

  41. Pazzani, M.J., Muramatsu, J., Billsus, D.: Syskill webert: Identifying interesting web sites. In: Proceedings of the National Conference on Artificial Intelligence (AAAI 1996), Portland, OR, USA, pp. 54–61. AAAI Press, Menlo Park (1996)

    Google Scholar 

  42. Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo (1988)

    Google Scholar 

  43. Pinkerton, B.: Finding what people want: Experiences with the webcrawler. In: Proceedings of the 2nd World Wide Web Conference (WWW2), Chicago, USA (1994)

    Google Scholar 

  44. Pryor, M.H.: The effects of singular value decomposition on collaborative filtering. Technical report, Hanover, NH, USA (1998)

    Google Scholar 

  45. Quillian, R.M.: Semantic memory. In: Minsky, M. (ed.) Semantic information processing, pp. 216–270. The MIT Press, Cambridge (1968)

    Google Scholar 

  46. Rennie, J., McCallum, A.: Using reinforcement learning to spider the web efficiently. In: ICML 1999: Proceedings of the Sixteenth International Conference on Machine Learning, San Francisco, CA, USA, pp. 335–343. Morgan Kaufmann Publishers Inc., San Francisco (1999)

    Google Scholar 

  47. Robertson, S., Walker, S.: On relevance weights with little relevance information. In: Proceedings of the 20th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Relevance Feedback, pp. 16–24 (1997)

    Google Scholar 

  48. Sarwar, B.M., Karypis, G., Konstan, J.A., Riedl, J.T.: Application of dimensionality reduction in recommender systems - a case study. In: Web Mining for E-Commerce – Challenges and Opportunities, Boston, MA, USA (2000)

    Google Scholar 

  49. Savoy, J., Picard, J.: Retrieval effectiveness on the web. Information Processing & Management 37(4), 543–569 (2001)

    Article  MATH  Google Scholar 

  50. 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)

    Article  Google Scholar 

  51. Speretta, M., Gauch, S.: Personalized search based on user search histories. In: Web Intelligence (WI 2005), France. IEEE Computer Society, Los Alamitos (2005)

    Google Scholar 

  52. Sun, J.-T., Zeng, H.-J., Liu, H., Lu, Y., Chen, Z.: Cubesvd: A novel approach to personalized web search. In: WWW 2005: Proceedings of the 14th international conference on World Wide Web, pp. 382–390. ACM Press, New York (2005)

    Chapter  Google Scholar 

  53. Yuwono, B., Lam, S.L.Y., Ying, J.H., Lee, D.L.: A World Wide Web resource discovery system. In: Proceedings of the 4th World Wide Web Conference (WWW4), Boston, Massachusetts, USA, pp. 145–158 (1995)

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science and Automation, Artificial Intelligence Laboratory, University of “Roma Tre”, Via della Vasca Navale, 79 00146, Rome, Italy

    Alessandro Micarelli, Fabio Gasparetti & Claudio Biancalana

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  1. Alessandro Micarelli
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  2. Fabio Gasparetti
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  3. Claudio Biancalana
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Editors and Affiliations

  1. FBK-irst, I-38050, Povo, Trento, Italy

    Oliviero Stock

  2. Dipartimento di Informatica e Sistemistica, Università di Roma “La Sapienza”, Via Salaria 113, Roma,, Italia

    Marco Schaerf

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Micarelli, A., Gasparetti, F., Biancalana, C. (2006). Intelligent Search on the Internet. In: Stock, O., Schaerf, M. (eds) Reasoning, Action and Interaction in AI Theories and Systems. Lecture Notes in Computer Science(), vol 4155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11829263_14

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  • DOI: https://doi.org/10.1007/11829263_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-37901-0

  • Online ISBN: 978-3-540-37902-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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