Incorporating latent semantic indexing into a neural network model for information retrieval
Inien Syu, Sheau-Dong Lang, Narsingh Deo · 1996
We incorporate the Latent Semantic Indexing (LSl) technique into a competition-based neural network model for information retrieval.The original neural network model was based on a causal inference network, incorporating Roget's Thesaurus, that connects the index terms and related documents.Since the pmcIess of creating or updating a thesaurus is rather expensive, we apply the LSI technique to provide an automated procedure that captures the semantic relationship between the doctrments and index terms.C)ur experimental results using four standard text collections show that the LSI-baaed model generates appreciable improvement in retrieval effectiveness with faster query evaluation over the thesatrrus-ba~sed model.