By Topic

Using contextual semantics to automate the Web document search and analysis

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

3 Author(s)
Lian Wang ; Hong Kong Univ., China ; Song, W. ; Cheung, D.

Traditional information retrieval techniques require documents that share enough words to build semantic links between them. This kind of technique is greatly affected by two factors: synonymy (different words having the same meaning) and polysemy (a word with several meanings), also known as ambiguity. Synonymy may result in a loss of semantic difference, while polysemy may lead to wrong semantic links. S.J. Green (1999) proposed the concept of a synset (a set of words having the same or a close meaning) and used a synset method to solve the problems of synonymy and polysemy. Although the synonymy problem can be solved, the polysemy problem still remains, because it is not actually possible to use an entire document as a basis to identify the meaning of a word. In this paper, we propose the concept of a context-related semantic set in order to identify the meaning of a word by considering the relations between the word and its contexts. We believe that this approach can efficiently solve the ambiguity problem and hence support the automation of Web document searching and analysis

Published in:

Web Information Systems Engineering, 2000. Proceedings of the First International Conference on  (Volume:2 )

Date of Conference:

2000