Joint Extraction of Compound Entities and Relationships from Biomedical Literature

Author

Ramakrishnan, Cartic ; Mendes, Pablo N. ; Gama, Rodrigo A T S da ; Ferreira, Guilherme C N ; Sheth, Amit P.

Author_Institution

Dept. of Comput. Sci. & Eng., Wright State Univ., Dayton, OH

Volume

1

fYear

2008

fDate

9-12 Dec. 2008

Firstpage

398

Lastpage

401

Abstract

In this paper we identify some limitations of contemporary information extraction mechanisms in the context of biomedical literature. We present an extraction mechanism that generates structured representations of textual content. Our extraction mechanism achieves this by extracting compound entities, and relationships between them, occuring in text. A detailed evaluation of the relationship and compound entities extracted is presented. Our results show over 62% average precision across 8 relationship types tested with over 82% average precision for compound entity identification.

Keywords

data mining; information retrieval; medical administrative data processing; biomedical literature; compound entity identification; information extraction; structured representations; textual content; Biomedical engineering; Computer science; Data mining; Intelligent agent; Joining processes; Keyword search; Search engines; Search methods; Testing; Yarn; Complex entity extraction; Semantic Text mining; Text mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on

Conference_Location

Sydney, NSW

Print_ISBN

978-0-7695-3496-1

Type

conf

DOI

10.1109/WIIAT.2008.295

Filename

4740481