loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
21st International Conference on Data Engineering Workshops (ICDEW'05)
Using Medical Test Collection Relevance Judgements to Identify Ontological Relationships Useful for Query Expansion
Tokyo, Japan
April 05-April 08
ISBN: 0-7695-2657-8
ASCII Text
x 
 
D. Wollersheim, W. J. Rahayu, "Using Medical Test Collection Relevance Judgements to Identify Ontological Relationships Useful for Query Expansion," Data Engineering Workshops, 22nd International Conference on, pp. 1160, 21st International Conference on Data Engineering Workshops (ICDEW'05), 2005.
 
 
BibTex
x
 
@article{ 10.1109/ICDE.2005.300,
author = {D. Wollersheim and W. J. Rahayu},
title = {Using Medical Test Collection Relevance Judgements to Identify Ontological Relationships Useful for Query Expansion},
journal ={Data Engineering Workshops, 22nd International Conference on},
volume = {0},
year = {2005},
isbn = {0-7695-2657-8},
pages = {1160},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDE.2005.300},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Data Engineering Workshops, 22nd International Conference on
TI - Using Medical Test Collection Relevance Judgements to Identify Ontological Relationships Useful for Query Expansion
SN - 0-7695-2657-8
SP
EP
A1 - D. Wollersheim,
A1 - W. J. Rahayu,
PY - 2005
KW - null
VL - 0
JA - Data Engineering Workshops, 22nd International Conference on
ER -
 
D. Wollersheim, La Trobe University,Melbourne, Australia
W. J. Rahayu, La Trobe University,Melbourne, Australia
In this paper we describe an innovative query expansion evaluation framework (QEEF) which discovers the ontological and algorithmic characteristics that drive successful query expansion. The method consists of identifying UMLS (Unified Medical Language System) concepts in the Ohsumed corpus queries and documents, and then applying variety of query expansion algorithms to the query concepts, both individually and at the query level. We analyse the results, discovering the characteristics of high relevance medical query expansions. We directly evaluate query expansion success, and this enables discovery of the relationship between the UMLS facets and this success. The paper details the methods used, and then discusses the influence of both UMLS attributes, and choice of query expansion algorithm, on query expansion success.
Citation:
D. Wollersheim, W. J. Rahayu, "Using Medical Test Collection Relevance Judgements to Identify Ontological Relationships Useful for Query Expansion," icdew, pp.1160, 21st International Conference on Data Engineering Workshops (ICDEW'05), 2005
Usage of this product signifies your acceptance of the Terms of Use.