This work focuses on understanding the user intent in the
medical domain. The combination of Semantic Web and in-
formation retrieval technologies promises a better compre-
hension of user intents. Mapping queries to entities using
Freebase is not novel, but so far only one entity per query
could be identified. We overcome this limitation using anno-
tations provided by Metamap. Also, different approaches to
map queries to Freebase are explored and evaluated. We
propose an indirect evaluation of the mappings, through
user intent defined by classes such as Symptoms, Diseases or
Treatments. Our experiments show that by using the con-
cepts annotated by Metamap it is possible to improve the
accuracy and F1 performances of mappings from queries to
Freebase entities.
%0 Conference Paper
%1 hanbury2014intent
%A Palotti, João
%A Stefanov, Veronika
%A Hanbury, Allan
%B Information Interaction in Context conference (IIiX) 2014
%D 2014
%K healthsearch khresmoi-project myown
%T User intent behind medical queries: An evaluation of entity
mapping approaches with Metamap and Freebase
%X This work focuses on understanding the user intent in the
medical domain. The combination of Semantic Web and in-
formation retrieval technologies promises a better compre-
hension of user intents. Mapping queries to entities using
Freebase is not novel, but so far only one entity per query
could be identified. We overcome this limitation using anno-
tations provided by Metamap. Also, different approaches to
map queries to Freebase are explored and evaluated. We
propose an indirect evaluation of the mappings, through
user intent defined by classes such as Symptoms, Diseases or
Treatments. Our experiments show that by using the con-
cepts annotated by Metamap it is possible to improve the
accuracy and F1 performances of mappings from queries to
Freebase entities.
@inproceedings{hanbury2014intent,
abstract = {This work focuses on understanding the user intent in the
medical domain. The combination of Semantic Web and in-
formation retrieval technologies promises a better compre-
hension of user intents. Mapping queries to entities using
Freebase is not novel, but so far only one entity per query
could be identified. We overcome this limitation using anno-
tations provided by Metamap. Also, different approaches to
map queries to Freebase are explored and evaluated. We
propose an indirect evaluation of the mappings, through
user intent defined by classes such as Symptoms, Diseases or
Treatments. Our experiments show that by using the con-
cepts annotated by Metamap it is possible to improve the
accuracy and F1 performances of mappings from queries to
Freebase entities.},
added-at = {2014-07-30T13:46:28.000+0200},
author = {Palotti, João and Stefanov, Veronika and Hanbury, Allan},
biburl = {https://www.bibsonomy.org/bibtex/20e68291156d20629eee805bf076f8ef9/joaopalotti},
booktitle = {Information Interaction in Context conference (IIiX) 2014},
interhash = {4358ab04fecfa16b8d67efab0a7d9fdb},
intrahash = {0e68291156d20629eee805bf076f8ef9},
keywords = {healthsearch khresmoi-project myown},
timestamp = {2014-07-30T13:48:05.000+0200},
title = {User intent behind medical queries: An evaluation of entity
mapping approaches with Metamap and Freebase},
year = 2014
}