Improving text retrieval for the routing problem using latent semantic indexing (1994)
| Venue: | In Proc. of the 17th ACM-SIGIR Conference |
| Citations: | 83 - 2 self |
BibTeX
@INPROCEEDINGS{Hull94improvingtext,
author = {David Hull},
title = {Improving text retrieval for the routing problem using latent semantic indexing},
booktitle = {In Proc. of the 17th ACM-SIGIR Conference},
year = {1994},
pages = {282--291}
}
Years of Citing Articles
Bookmark
 |
 |
 |
 |
 |
 |
OpenURL
Abstract
Latent Semantic Indexing (LSI) is a novel approach to information retrieval that attempts to model the underlying structure of term associations by transforming the traditional representation of documents as vectors of weighted term frequencies to a new coordinate space where both documents and terms are represented as linear combinations of underlying semantic factors. In previous research, LSI has produced a small improvement in retrieval performance. In this paper, we apply LSI to the routing task, which operates under the assumption that a sample of relevant and non-relevant documents is available to use in constructing the query. Once again, LSI slightly improves performance. However, when LSI is used is conduction with statistical classification, there is a dramatic improvement in performance. 1
