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Concept mining is an activity that results in the extraction of concepts from artifacts. Solutions to the task typically involve aspects of artificial intelligence and statistics, such as data mining and text mining.〔Yuen-Hsien Tseng, Chun-Yen Chang, Shu-Nu Chang Rundgren, and Carl-Johan Rundgren, " Mining Concept Maps from News Stories for Measuring Civic Scientific Literacy in Media", Computers and Education, Vol. 55, No. 1, August 2010, pp. 165-177.〕 Because artifacts are typically a loosely structured sequence of words and other symbols (rather than concepts), the problem is nontrivial, but it can provide powerful insights into the meaning, provenance and similarity of documents. ==Methods== Traditionally, the conversion of words to concepts has been performed using a thesaurus,〔Yuen-Hsien Tseng, " Automatic Thesaurus Generation for Chinese Documents", Journal of the American Society for Information Science and Technology, Vol. 53, No. 13, Nov. 2002, pp. 1130-1138.〕 and for computational techniques the tendency is to do the same. The thesauri used are either specially created for the task, or a pre-existing language model, usually related to Princeton's WordNet. The mappings of words to concepts〔Yuen-Hsien Tseng, " Generic Title Labeling for Clustered Documents", Expert Systems With Applications, Vol. 37, No. 3, 15 March 2010, pp. 2247-2254 .〕 are often ambiguous. Typically each word in a given language will relate to several possible concepts. Humans use context to disambiguate the various meanings of a given piece of text, where available machine translation systems cannot easily infer context. For the purposes of concept mining however, these ambiguities tend to be less important than they are with machine translation, for in large documents the ambiguities tend to even out, much as is the case with text mining. There are many techniques for disambiguation that may be used. Examples are linguistic analysis of the text and the use of word and concept association frequency information that may be inferred from large text corpora. Recently, techniques that base on semantic similarity between the possible concepts and the context have appeared and gained interest in the scientific community. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Concept mining」の詳細全文を読む スポンサード リンク
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