A heuristic information retrieval model on a massively parallel processor

We adapt a competition-based connectionist model to information retrieval. This model, which has been proposed for diagnostic problem solving, treats documents as "disorders" and user information needs as "manifestations", and it uses a competitive activation mechanism which conv...

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Bibliographic Details
Published inProceedings of the Eleventh International Conference on Data Engineering pp. 365 - 372
Main Authors Inien Syu, Lang, S.D., Hua, K.A.
Format Conference Proceeding
LanguageEnglish
Published IEEE Comput. Soc. Press 1995
Subjects
Bayesian methods
Computer networks
Computer science
Content based retrieval
Heuristic algorithms
Information retrieval
Machine assisted indexing
Natural languages
Problem-solving
Vocabulary
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Summary:We adapt a competition-based connectionist model to information retrieval. This model, which has been proposed for diagnostic problem solving, treats documents as "disorders" and user information needs as "manifestations", and it uses a competitive activation mechanism which converges to a set of disorders that best explain the given manifestations. Our experimental results using four standard document collections demonstrate the efficiency and the retrieval precision of this model, comparable to or better than that of various information retrieval models reported in the literature. We also propose a parallel implementation of the model on a SIMD machine, MasPar's MP-I. Our experimental results demonstrate the potential to achieve significant speedups.< >
ISBN:0818669101
9780818669101
DOI:10.1109/ICDE.1995.380371