By Topic

Enabling concept-based relevance feedback for information retrieval on the WWW

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
$31 $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)
Chia-Hui Chang ; Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan ; Ching-Chi Hsu

The World Wide Web is a world of great richness, but finding information on the Web is also a great challenge. Keyword-based querying has been an immediate and efficient way to specify and retrieve related information that the user inquires. However, conventional document ranking based on an automatic assessment of document relevance to the query may not be the best approach when little information is given, as in most cases. In order to clarify the ambiguity of the short queries given by users, we propose the idea of concept-based relevance feedback for Web information retrieval. The idea is to have users give two to three times more feedback in the same amount of time that would be required to give feedback for conventional feedback mechanisms. Under this design principle, we apply clustering techniques to the initial search results to provide concept-based browsing. We show the performance of various feedback interface designs and compare their pros and cons. We measure precision and relative recall to show how clustering improves performance over conventional similarity ranking and, most importantly, we show how the assistance of concept-based presentation reduces browsing labor

Published in:

Knowledge and Data Engineering, IEEE Transactions on  (Volume:11 ,  Issue: 4 )