Intelligent Search on the Internet

  • Alessandro Micarelli
  • Fabio Gasparetti
  • Claudio Biancalana
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4155)


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.


Search Engine User Model Relevance Feedback Semantic Network Pheromone Trail 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Alessandro Micarelli
    • 1
  • Fabio Gasparetti
    • 1
  • Claudio Biancalana
    • 1
  1. 1.Department of Computer Science and Automation, Artificial Intelligence LaboratoryUniversity of “Roma Tre”RomeItaly

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