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Abstract
The vacabulary 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 internsive. In this
seminar, we propose and evaluate an efficient algorithm for the
incremental update of concept space. In our model, only strong
associations are maintained, since they are most useful in thesauri
construction. Our algorithm uses a pruning technique to avoid computing
weak associations to achieve efficiency.
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