TY - GEN
T1 - Retrieval of Semantically Similar Healthcare Questions in Healthcare Forums
AU - Wang, Yanshan
AU - Mehrabi, Saeed
AU - Mojarad, Majid Rastegar
AU - Li, Dingcheng
AU - Liu, Hongfang
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/8
Y1 - 2015/12/8
N2 - Healthcare forums are popular platforms for patients to communicate with other patients who have similar conditions. Retrieving similar post to a user's question is valuable as the question might have been already answered in similar threads. ICHI 2015 organized a challenge with a corpus of ninety-five selected questions and a query set of ten questions from various diabetes related online forums. The task in this challenge is that given the corpus, a system should be developed to generate the most three similar questions for each question in the query set. In order to accomplish the challenge, we utilized Elastic search to built and search an index based on tokens, UMLS concepts, and semantic types, and finally combined the ranking results with LDI, a Latent Dirichlet Allocation (LDA) based ranking method. The experimental results showed that a mean average precision of 0.72 was achieved on the manually created gold standard.
AB - Healthcare forums are popular platforms for patients to communicate with other patients who have similar conditions. Retrieving similar post to a user's question is valuable as the question might have been already answered in similar threads. ICHI 2015 organized a challenge with a corpus of ninety-five selected questions and a query set of ten questions from various diabetes related online forums. The task in this challenge is that given the corpus, a system should be developed to generate the most three similar questions for each question in the query set. In order to accomplish the challenge, we utilized Elastic search to built and search an index based on tokens, UMLS concepts, and semantic types, and finally combined the ranking results with LDI, a Latent Dirichlet Allocation (LDA) based ranking method. The experimental results showed that a mean average precision of 0.72 was achieved on the manually created gold standard.
KW - healthcare forum
KW - information retrieval
KW - question answering
UR - http://www.scopus.com/inward/record.url?scp=84966297192&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84966297192&partnerID=8YFLogxK
U2 - 10.1109/ICHI.2015.97
DO - 10.1109/ICHI.2015.97
M3 - Conference contribution
AN - SCOPUS:84966297192
T3 - Proceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015
SP - 517
EP - 518
BT - Proceedings - 2015 IEEE International Conference on Healthcare Informatics, ICHI 2015
A2 - Fu, Wai-Tat
A2 - Balakrishnan, Prabhakaran
A2 - Harabagiu, Sanda
A2 - Wang, Fei
A2 - Srivatsava, Jaideep
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd IEEE International Conference on Healthcare Informatics, ICHI 2015
Y2 - 21 October 2015 through 23 October 2015
ER -