Measuring similarities between technical terms based on Wikipedia
|Measuring similarities between technical terms based on Wikipedia|
|Author(s)||Hwang M., Jeong D.-H., Lee S., Jung H.|
|Published in||Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011|
|Keyword(s)||Similarity measure, Technical terms, Wikipedia category, Wikipedia internal link (Extra: Emerging technologies, Hybrid method, Query expansion, Semantic information, Similarity measure, Technical terms, Wikipedia, Word Sense Disambiguation, Data processing, Internet)|
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Measuring similarities between technical terms based on Wikipedia is a 2011 conference paper written in English by Hwang M., Jeong D.-H., Lee S., Jung H. and published in Proceedings - 2011 IEEE International Conferences on Internet of Things and Cyber, Physical and Social Computing, iThings/CPSCom 2011.
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-theart WLM (Wikipedia Link-based Measure) show that this proposed method works better than each single method.
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