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- W2334887407 abstract "This thesis solves the problem of the enhancement of the accuracy of opinion mining data by applying the filtering model of candidate sentiment vocabularies as a way of constructing a text mining-based sentiment dictionary to be applied in the Korean grammar structure. The fact the reliability of sensitive vocabularies shows huge variances according to the filtering modeling method applied has become a decreasing factor for the accuracy of the vocabularies in the opinion mining process, and this is primarily due to the fact there isn't a success factor in the filtering modeling standard for precise selection of vocabularies. In this thesis, a text filtering modeling for the selection of candidate sentiment vocabularies of the processed Korean grammar were suggested to solve such problems. Moreover, a filtering model of positive and negative vocabularies on candidate Korean sentiment vocabularies and a reliability scale for accuracy were suggested in this thesis by applying the semi- structured data filtering model." @default.
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- W2334887407 date "2015-10-31" @default.
- W2334887407 modified "2023-09-27" @default.
- W2334887407 title "Classification Technique for Filtering Sentiment Vocabularies for the Enhancement of Accuracy of Opinion Mining" @default.
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- W2334887407 doi "https://doi.org/10.14257/ijunesst.2015.8.10.02" @default.
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