Efficient Algorithms for Concept Space Construction

Authors:
Chi-Yuen Ng;Joseph Lee;Felix Cheung;Ben Kao;David Wai-Lok Cheung
Affiliations:
-;-;-;-;-
Venue:
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Year:
2001

Citing 5
Cited 0

The vocabulary problem in human-system communication

Communications of the ACM
Information retrieval: data structures and algorithms

Information retrieval: data structures and algorithms
Interactive term suggestion for users of digital libraries: using subject thesauri and co-occurrence lists for information retrieval

Proceedings of the first ACM international conference on Digital libraries
A concept space approach to addressing the vocabulary problem in scientific information retrieval: an experiment on the worm community system

Journal of the American Society for Information Science
Modern Information Retrieval

Modern Information Retrieval

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Abstract

The vocabulary problem in information retrieval arises because authors and indexers often use different terms for the same concept. A thesaurus defines mappings between different but related terms. It is widely used in modern information retrieval systems to solve the vocabulary problem. Chen et al. proposed the concept space approach to automatic thesaurus construction. A concept space contains the associations between every pair of terms. Previous research studies show that concept space is a useful tool for helping information searchers in revising their queries in order to get better results from information retrieval systems. The construction of a concept space, however, is very computationally intensive. In this paper, we propose and evaluate efficient algorithms for constructing concept spaces that include only strong associations. Since weak associations are not useful in thesauri construction, our algorithms use various prunning techniques to avoid computing weak associations to achieve efficiency.