Using document dimensions for enhanced information retrieval

T Jayasooriya; S Manandhar

Using document dimensions for enhanced information retrieval

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

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 game 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.

Original language	English
Title of host publication	APPLIED COMPUTING, PROCEEDINGS
Editors	S Manandhar, J Austin, U Desai, Y Oyanagi, A Talukder
Place of Publication	BERLIN
Publisher	Springer
Pages	145-152
Number of pages	8
ISBN (Print)	3-540-23659-7
Publication status	Published - 2004
Event	2nd Asian Applied Computing Conference - Kathmandu Duration: 29 Oct 2004 → 31 Oct 2004

Conference

Conference	2nd Asian Applied Computing Conference
City	Kathmandu
Period	29/10/04 → 31/10/04

Cite this

@inproceedings{a63e306d20eb441bbce799924d2048d6,

title = "Using document dimensions for enhanced information retrieval",

abstract = "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 game 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.",

author = "T Jayasooriya and S Manandhar",

year = "2004",

language = "English",

isbn = "3-540-23659-7",

pages = "145--152",

editor = "S Manandhar and J Austin and U Desai and Y Oyanagi and A Talukder",

booktitle = "APPLIED COMPUTING, PROCEEDINGS",

publisher = "Springer",

address = "Germany",

note = "2nd Asian Applied Computing Conference ; Conference date: 29-10-2004 Through 31-10-2004",

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TY - GEN

T1 - Using document dimensions for enhanced information retrieval

AU - Jayasooriya, T

AU - Manandhar, S

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 game 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 game 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.

M3 - Conference contribution

SN - 3-540-23659-7

SP - 145

EP - 152

BT - APPLIED COMPUTING, PROCEEDINGS

A2 - Manandhar, S

A2 - Austin, J

A2 - Desai, U

A2 - Oyanagi, Y

A2 - Talukder, A

PB - Springer

CY - BERLIN

T2 - 2nd Asian Applied Computing Conference

Y2 - 29 October 2004 through 31 October 2004

ER -