By Topic

Cache adaptation of internet services and user modelling for improving ranking precision in third-party results

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Ioannis Anagnostopoulos ; Univ. of the Aegean, Karlovassi ; Christos Anagnostopoulos

This paper proposes a meta-search algorithm, which adapts to the user browsing behavior during his search sessions. In parallel, the algorithm is capable of monitoring the ability of its third-party search services in terms of refreshing and updating the content of their indexes. The algorithm uses five well known Web search services namely AltaVista, Google, Lycos, MSN, and Yahoo!. The assessments made verified the robustness of our proposal, since we measured a significant improvement in the precision of the unified third-party results, especially for the lower recall levels where the user explores the top-ranked information. In addition, through capture recapture experiments we observed that Google, MSN and Yahoo! managed to adapt more adequately in the incessant evolution of the web, since they achieved higher freshness rates, managing in parallel to provide more validated active results to the end users.

Published in:

Semantic Media Adaptation and Personalization, Second International Workshop on

Date of Conference:

17-18 Dec. 2007