DocumentCode
653504
Title
Extracting Protein Terminologies in Literatures
Author
Jangwon Gim ; Kim, D.J. ; Myunggwon Hwang ; Sa-kwang Song ; Do-Heon Jeong ; Hanmin Jung
Author_Institution
Dept. of Comput. Intell. Res., Korea Inst. of Sci. & Technol. Inf., Daejeon, South Korea
fYear
2013
fDate
20-23 Aug. 2013
Firstpage
2136
Lastpage
2140
Abstract
Recently, key terminologies in literatures play an important role in analyzing and predicting research trends. Extracting those terminologies therefore used in the papers of researchers´ has become the most major issue in a variety of fields. To extract those terminologies, dictionary-based approach that contains terminologies has been applied. Wikipedia also can be considered as a dictionary since Wikipedia has abundant terminologies and power of the collective intelligence. It means that the terminologies are continuously modified and extended every day. Thus it could be an answer set to compare with the terminologies in literatures. However, it hardly extracts terminologies that are newly defined and coined by researchers. In order to solve this issue, we propose a method to derive a set of terminology candidates by comparing terminologies in literatures and Wikipedia. The candidate set extracted from the method showed an accuracy of about 64.33%, which is a good result as an initial study.
Keywords
Web sites; biology computing; dictionaries; proteins; Wikipedia; abundant terminologies; answer set; collective intelligence; dictionary based approach; protein terminologies; research trends; Electronic publishing; Encyclopedias; Internet; Protein engineering; Proteins; Terminology; Wikipedia terminologis; keyword refinement; protein terminologies;
fLanguage
English
Publisher
ieee
Conference_Titel
Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing
Conference_Location
Beijing
Type
conf
DOI
10.1109/GreenCom-iThings-CPSCom.2013.402
Filename
6682412
Link To Document