Guidelines for Web Search Engines: From Searching and Filtering to Interface

In this paper we address a set of important guidelines that web search engines should follow in order to become effective. We refer to the importance of semantic web in the section of search engines which comes up from the better set-up that ontologies offer. Moreover, some of the most known and adaptive learning techniques are described in order to personalize web search engines, including methods for implicit and explicit feedback. In addition, we focus on how these methods can coexist so as to achieve high performance and we investigate the role of metadata in web searching in order to detect user interests and improve the information filtering procedure. Finally, we propose how these can be combined and presented into an interface, which will be considered as user friendly.


Search Engine User Profile Relevance Feedback Query Expansion User Interest 


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Computer Engineering and Informatics DepartmentUniversity of PatrasPatrasGreece
  2. 2.Open Research Society

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