A Cooperative Paradigm for Fighting Information Overload

  • Daniel Gayo-Avello
  • Darío Álvarez-Gutiérrez
  • José Gayo-Avello
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2869)


The Web is mainly processed by humans. The role of the machines is just to transmit and display the contents of the documents, barely being able to do something else. Nowadays there are lots of initiatives trying to change this situation; many of them are related to fields like the Semantic Web [1] or Web Intelligence. In this paper we describe the Cooperative Web [2] that can be seen as a new proposal towards Web Intelligence. The Cooperative Web would allow us to extract semantics from the Web in an automatic way, without the need of ontological artifacts, with language independence and, besides of this, allowing the usage of browsing experience from individual users to serve the whole community of users.


Search Engine Utility Level Software Agent Collaborative Filter Information Overload 
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.


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  1. 1.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284(5), 34–43 (2001)CrossRefGoogle Scholar
  2. 2.
    Gayo-Avello, D., Álvarez-Gutiérrez, D.: The Cooperative Web: A Complement to the Semantic Web. In: Proc. of 26th Annual International Computer Software and Applications Conference, Oxford, England, pp. 179–183 (2002)Google Scholar
  3. 3.
    Furnas, G.W., Landauer, T.K., Gómez, L.M., Dumais, S.T.: The vocabulary problem in human-system communication. CACM 30(11), 964–971 (1987)Google Scholar
  4. 4.
    Pinkerton, B.: Finding what people want: Experiences with the WebCrawler. In: Proc. of the Second International World Wide Web Conference, Chicago, IL, USA (1994)Google Scholar
  5. 5.
    Krovetz, R., Croft, W.B.: Lexical Ambiguity and Information Retrieval. ACM Transactions on Information Systems 10(2), 115–141 (1992)CrossRefGoogle Scholar
  6. 6.
    Berners-Lee, T.: Information Management: A Proposal (1989),
  7. 7.
    Koster, M.: ALIWEB: Archie-Like indexing in the Web. Computer Networks and ISDN Systems 27(2), 175–182 (1994)CrossRefGoogle Scholar
  8. 8.
    Mauldin, M.L., Leavitt, J.R.R.: Web agent related research at the Center for Machine Translation. In: Proc. of the ACM Special Interest Group on Networked Information Discovery and Retrieval (ACM-SIGNIDR-V), McLean, VA, USA (1994)Google Scholar
  9. 9.
    Kleinberg, J.M.: Authoritative Sources in a Hyperlinked Environment. In: Proc. of the 9th Annual ACM-SIAM Symposium on Discrete Algorithms, San Francisco, CA, USA (1998)Google Scholar
  10. 10.
    Page, L., Brin, S., Motwani, R., Winograd, T.: The PageRank Citation Ranking: Bringing Order to the Web. Stanford Digital Libraries Working Paper (1998)Google Scholar
  11. 11.
    Morita, M., Shinoda, Y.: Information filtering based on user behavior analysis and best match text retrieval. In: Proc. of the 17th Annual International Retrieval, Dublin, Ireland (1994)Google Scholar
  12. 12.
    Maes, P.: Agents that Reduce Work and Information Overload. CACM 37(7), 811–821 (1994)Google Scholar
  13. 13.
    Lieberman, H.: Letizia: An Agent That Assists Web Browsing. In: Proc. of the 14th International Joint Conference on Artificial Intelligence, Montreal, QC, Canada (1995)Google Scholar
  14. 14.
    Starr, B., Ackerman, M.S., Pazzani, M.: Do-I-Care: A Collaborative Web Agent. In: Proc. of the ACM on Human Factors in Computing Systems, Vancouver, Canada, pp. 273–274 (1996)Google Scholar
  15. 15.
    Balabanovic, M.: An interface for learning multi-topic user profiles from implicit feedback. In: Proc. of AAAI Workshop on Recommender Systems, Madison, WI, USA (1998)Google Scholar
  16. 16.
    Luke, S., Spector, L., Rager, D.: Ontology-Based Knowledge Discovery on the World-Wide Web. In: Working Notes of the Workshop on Internet-Based Information Systems at the 13th National Conference on Artificial Intelligence (AAAI 1996) (1996)Google Scholar
  17. 17.
    Craven, M., DiPasquo, D., Freitag, D., McCallum, A., Mitchell, T., Nigam, K., Slattery, S.: Learning to Extract Symbolic Knowledge from the World Wide Web. In: Proc. of the 15th National Conference on Artificial Intelligence (AAAI 1998), Madison, WI, USA (1998)Google Scholar
  18. 18.
    Fensel, D., Decker, S., Erdmann, M., Studer, R.: Ontobroker: Or How to Enable Intelligent Access to the WWW. In: Proc. of the 11th Workshop on Knowledge Acquisition, Modeling, and Management, Banff, Canada (1998)Google Scholar
  19. 19.
    Marchiori, M., Saarela, J.: Query + Metadata + Logic = Metalog. In: Proc. of Query Languages Workshop, Boston, MA, USA (1998)Google Scholar
  20. 20.
    Brickley, D., Miller, L.: RDF: Extending and Querying RSS channels. ILRT discussion document (2000),
  21. 21.
    Decker, S., Brickley, D., Saarela, J., Angele, J.: A Query and Inference Service for RDF. In: Proc. of Query Languages Workshop, Boston, MA, USA (1998)Google Scholar
  22. 22.
    Karvounarakis, G., Christophides, V., Plexousakis, D., Alexaki, S.: Querying RDF Descriptions for Community Web Portals. In: The French National Conference on Databases, Agadir, Maroc (2001)Google Scholar
  23. 23.
    Maedche, A., Staab, S.: Discovering Conceptual Relations from Text. Technical Report 399”. Institute AIFB, Karlsruhe University (2000)Google Scholar
  24. 24.
    Erdmann, M., Maedche, A., Scnurr, H.P., Staab, S.: From Manual to Semi-automatic Semantic Annotation: About Ontology-based Text Annotation Tools. ETAI Journal - Section on Semantic Web (Linköping Electronic Articles in Computer and Information Science) 6 (2001)Google Scholar
  25. 25.
    Fensel, D.: Ontology-Based Knowledge Management. IEEE Computer 35(11), 56–59 (2002)Google Scholar
  26. 26.
    Nishida, T.: Social Intelligence Design for the Web. IEEE Computer 35(11), 37–41 (2002)Google Scholar
  27. 27.
    Han, J., Chang, K.C.-C.: Data Mining for Web Intelligence. IEEE Computer 35(11), 64–70 (2002)Google Scholar
  28. 28.
    Cercone, N., Hou, L., Keselj, V., An, A., Naruedomkul, K., Hu, X.: From Computational Intelligence to Web Intelligence. IEEE Computer 35(11), 72–76 (2002)Google Scholar
  29. 29.
    Foltz, P.W.: Using Latent Semantic Indexing for Information Filtering. In: Proc. of the ACM Conference on Office Information Systems, Boston, USA, pp. 40–47 (1990)Google Scholar
  30. 30.
    Karypis, G., Han, E.: Concept indexing: A fast dimensionality reduction algorithm with applications to document retrieval and categorization. Technical Report TR-00-0016. University of Minnesota (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Daniel Gayo-Avello
    • 1
  • Darío Álvarez-Gutiérrez
    • 1
  • José Gayo-Avello
    • 1
  1. 1.Department of InformaticsUniversity of OviedoOviedoSPAIN

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