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A concept search (or conceptual search) is an automated information retrieval method that is used to search electronically stored unstructured text (for example, digital archives, email, scientific literature, etc.) for information that is conceptually similar to the information provided in a search query. In other words, the ''ideas'' expressed in the information retrieved in response to a concept search query are relevant to the ideas contained in the text of the query. ==Why Concept Search?== Concept search techniques were developed because of limitations imposed by classical Boolean keyword search technologies when dealing with large, unstructured digital collections of text. Keyword searches often return results that include many non-relevant items (false positives) or that exclude too many relevant items (false negatives) because of the effects of synonymy and polysemy. Synonymy means that one of two or more words in the same language have the same meaning, and polysemy means that many individual words have more than one meaning. Polysemy is a major obstacle for all computer systems that attempt to deal with human language. In English, most frequently used terms have several common meanings. For example, the word fire can mean: a combustion activity; to terminate employment; to launch, or to excite (as in fire up). For the 200 most-polysemous terms in English, the typical verb has more than twelve common meanings, or senses. The typical noun from this set has more than eight common senses. For the 2000 most-polysemous terms in English, the typical verb has more than eight common senses and the typical noun has more than five.〔Bradford, R. B., Word Sense Disambiguation, Content Analyst Company, LLC, U.S. Patent 7415462, 2008.〕 In addition to the problems of polysemous and synonymy, keyword searches can exclude inadvertently misspelled words as well as the variations on the stems (or roots) of words (for example, strike vs. striking). Keyword searches are also susceptible to errors introduced by optical character recognition (OCR) scanning processes, which can introduce random errors into the text of documents (often referred to as noisy text) during the scanning process. A concept search can overcome these challenges by employing word sense disambiguation (WSD),〔R. Navigli, (Word Sense Disambiguation: A Survey ), ACM Computing Surveys, 41(2), 2009.〕 and other techniques, to help it derive the actual meanings of the words, and their underlying concepts, rather than by simply matching character strings like keyword search technologies. 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 search」の詳細全文を読む スポンサード リンク
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