Title
Heuristic Information Retrieval Model On A Massively Parallel Processor
Abstract
We adapt a competition-based connectionist model to information retrieval in this paper. This model, which has been proposed for diagnostic problem solving, treats documents are treated 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 4 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.
Publication Date
1-1-1995
Publication Title
Proceedings - International Conference on Data Engineering
Number of Pages
365-372
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0029222554 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0029222554
STARS Citation
Syu, Inien; Lang, S. D.; and Hua, Kien A., "Heuristic Information Retrieval Model On A Massively Parallel Processor" (1995). Scopus Export 1990s. 1908.
https://stars.library.ucf.edu/scopus1990/1908