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 an efficient algorithm for the incremental update of concept spaces. 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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