Using Document Dimensions for Enhanced Information Retrieval

TY - CONF

T1 - Using Document Dimensions for Enhanced Information Retrieval

AU - Jayasooriya, Thimal

AU - Manandhar, Suresh

PY - 2004

Y1 - 2004

N2 - Conventional document search techniques are constrained by attempting to match individual keywords or phrases to source documents. Thus, these techniques miss out documents that contain semantically similar terms, thereby achieving a relatively low degree of recall. At the same time, processing capabilities and tools for syntactic and semantic analysis of language have advanced to the point where an index-time linguistic analysis of source documents is both feasible and realistic. In this paper, we introduce document dimensions, a means of classifying or grouping terms discovered in documents. Using an enhanced version of Jakarta Lucene[1], we demonstrate that supplementing keyword analysis with some syntactic and semantic information can indeed enhance the quality of information retrieval results.

AB - Conventional document search techniques are constrained by attempting to match individual keywords or phrases to source documents. Thus, these techniques miss out documents that contain semantically similar terms, thereby achieving a relatively low degree of recall. At the same time, processing capabilities and tools for syntactic and semantic analysis of language have advanced to the point where an index-time linguistic analysis of source documents is both feasible and realistic. In this paper, we introduce document dimensions, a means of classifying or grouping terms discovered in documents. Using an enhanced version of Jakarta Lucene[1], we demonstrate that supplementing keyword analysis with some syntactic and semantic information can indeed enhance the quality of information retrieval results.

U2 - 10.1007/978-3-540-30176-9_19

DO - 10.1007/978-3-540-30176-9_19

M3 - Paper

SP - 145

EP - 152

ER -