Topic analysis for psychiatric document retrieval

Liang Chih Yu, Chung Hsien Wu, Chin Yew Lin, Eduard Hovy, Chia Ling Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Psychiatric document retrieval attempts to help people to efficiently and effectively locate the consultation documents relevant to their depressive problems. Individuals can understand how to alleviate their symptoms according to recommendations in the relevant documents. This work proposes the use of high-level topic information extracted from consultation documents to improve the precision of retrieval results. The topic information adopted herein includes negative life events, depressive symptoms and semantic relations between symptoms, which are beneficial for better understanding of users' queries. Experimental results show that the proposed approach achieves higher precision than the word-based retrieval models, namely the vector space model (VSM) and Okapi model, adopting word-level information alone.

Original languageEnglish
Title of host publicationACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics
Pages1024-1031
Number of pages8
Publication statusPublished - 2007 Dec 1
Event45th Annual Meeting of the Association for Computational Linguistics, ACL 2007 - Prague, Czech Republic
Duration: 2007 Jun 232007 Jun 30

Publication series

NameACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics

Other

Other45th Annual Meeting of the Association for Computational Linguistics, ACL 2007
CountryCzech Republic
CityPrague
Period07-06-2307-06-30

Fingerprint

semantics
event
Vector Space Model
Depressive Symptoms
Life Events
Semantic Relations

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language

Cite this

Yu, L. C., Wu, C. H., Lin, C. Y., Hovy, E., & Lin, C. L. (2007). Topic analysis for psychiatric document retrieval. In ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (pp. 1024-1031). (ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics).
Yu, Liang Chih ; Wu, Chung Hsien ; Lin, Chin Yew ; Hovy, Eduard ; Lin, Chia Ling. / Topic analysis for psychiatric document retrieval. ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics. 2007. pp. 1024-1031 (ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics).
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title = "Topic analysis for psychiatric document retrieval",
abstract = "Psychiatric document retrieval attempts to help people to efficiently and effectively locate the consultation documents relevant to their depressive problems. Individuals can understand how to alleviate their symptoms according to recommendations in the relevant documents. This work proposes the use of high-level topic information extracted from consultation documents to improve the precision of retrieval results. The topic information adopted herein includes negative life events, depressive symptoms and semantic relations between symptoms, which are beneficial for better understanding of users' queries. Experimental results show that the proposed approach achieves higher precision than the word-based retrieval models, namely the vector space model (VSM) and Okapi model, adopting word-level information alone.",
author = "Yu, {Liang Chih} and Wu, {Chung Hsien} and Lin, {Chin Yew} and Eduard Hovy and Lin, {Chia Ling}",
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language = "English",
isbn = "9781932432862",
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Yu, LC, Wu, CH, Lin, CY, Hovy, E & Lin, CL 2007, Topic analysis for psychiatric document retrieval. in ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics. ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics, pp. 1024-1031, 45th Annual Meeting of the Association for Computational Linguistics, ACL 2007, Prague, Czech Republic, 07-06-23.

Topic analysis for psychiatric document retrieval. / Yu, Liang Chih; Wu, Chung Hsien; Lin, Chin Yew; Hovy, Eduard; Lin, Chia Ling.

ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics. 2007. p. 1024-1031 (ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Topic analysis for psychiatric document retrieval

AU - Yu, Liang Chih

AU - Wu, Chung Hsien

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AU - Hovy, Eduard

AU - Lin, Chia Ling

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N2 - Psychiatric document retrieval attempts to help people to efficiently and effectively locate the consultation documents relevant to their depressive problems. Individuals can understand how to alleviate their symptoms according to recommendations in the relevant documents. This work proposes the use of high-level topic information extracted from consultation documents to improve the precision of retrieval results. The topic information adopted herein includes negative life events, depressive symptoms and semantic relations between symptoms, which are beneficial for better understanding of users' queries. Experimental results show that the proposed approach achieves higher precision than the word-based retrieval models, namely the vector space model (VSM) and Okapi model, adopting word-level information alone.

AB - Psychiatric document retrieval attempts to help people to efficiently and effectively locate the consultation documents relevant to their depressive problems. Individuals can understand how to alleviate their symptoms according to recommendations in the relevant documents. This work proposes the use of high-level topic information extracted from consultation documents to improve the precision of retrieval results. The topic information adopted herein includes negative life events, depressive symptoms and semantic relations between symptoms, which are beneficial for better understanding of users' queries. Experimental results show that the proposed approach achieves higher precision than the word-based retrieval models, namely the vector space model (VSM) and Okapi model, adopting word-level information alone.

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Yu LC, Wu CH, Lin CY, Hovy E, Lin CL. Topic analysis for psychiatric document retrieval. In ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics. 2007. p. 1024-1031. (ACL 2007 - Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics).