By Topic

Improving Document Search by Finding Domain Experts

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

4 Author(s)
Xiaomei Xu ; Sch. of Comput. Sci., Beijing Inst. of Technol., Beijing, China ; Feifei Zhang ; Xiaoyun Wang ; Xiaodan Zhang

Domain experts are important clues to search for relevant documents in digital library information system. In this paper, we present a method to improve the document search by finding domain experts. Our method aims at exploiting the domain expertise as a rich source of evidence for document search. In particular, we propose (i) a graph-based model of the domain experts, (ii) an algorithm to find the experts based on this model, and (iii) a novel probabilistic framework to incorporate the expert information into document search. In the experiments, we find that the conditional probability of document relevance on domain expert, i.e. P(D|e, q), follows a geometric distribution. The Experimental evaluation also demonstrates that the expert-based document search greatly increase the retrieval effectiveness.

Published in:

Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on  (Volume:3 )

Date of Conference:

21-22 Nov. 2009