Title :
Measuring Similarities between Technical Terms Based on Wikipedia
Author :
Hwang, Myunggwon ; Jeong, Do-Heon ; Lee, Seungwoo ; Jung, Hanmin
Author_Institution :
Dept. of Inf. Technol. Res., Korea Inst. of Sci. & Technol. Inf. (KISTI), Daejeon, South Korea
Abstract :
Measuring similarities between terms is useful for semantic information processing such as query expansion and WSD (Word Sense Disambiguation). This study aims at identifying technologies closely related to emerging technologies. Thus, we propose a hybrid method using both category and internal link information in Wikipedia, which is the largest database that everyone can share and edit its contents. Comparative experimental results with a state-of-the art WLM (Wikipedia Link-based Measure) show that this proposed method works better than each single method.
Keywords :
Web sites; natural language processing; query processing; text analysis; WLM; WSD; Wikipedia link-based measure; internal link information; query expansion; semantic information processing; similarity measurement; technical term; word sense disambiguation; Electronic publishing; Encyclopedias; Internet; Natural language processing; Out of order; Semantics; Similarity Measure; Technical Terms; Wikipedia Category; Wikipedia InterLink;
Conference_Titel :
Internet of Things (iThings/CPSCom), 2011 International Conference on and 4th International Conference on Cyber, Physical and Social Computing
Conference_Location :
Dalian
Print_ISBN :
978-1-4577-1976-9
DOI :
10.1109/iThings/CPSCom.2011.38