文章基本信息

标题：A Fuzzy Logic Based Sentiment Classification
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作者：J.I.Sheeba ; Dr.K.Vivekanandan
期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2014
卷号：4
期号：4
页码：27
DOI：10.5121/ijdkp.2014.4403
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Sentiment classification aims to detect information such as opinions, explicit , implicit feelings expressedin text. The most existing approaches are able to detect either explicit expressions or implicit expressions ofsentiments in the text separately. In this proposed framework it will detect both Implicit and Explicitexpressions available in the meeting transcripts. It will classify the Positive, Negative, Neutral words andalso identify the topic of the particular meeting transcripts by using fuzzy logic. This paper aims to addsome additional features for improving the classification method. The quality of the sentiment classificationis improved using proposed fuzzy logic framework .In this fuzzy logic it includes the features like Fuzzyrules and Fuzzy C-means algorithm.The quality of the output is evaluated using the parameters such asprecision, recall, f-measure. Here Fuzzy C-means Clustering technique measured in terms of Purity andEntropy. The data set was validated using 10-fold cross validation method and observed 95% confidenceinterval between the accuracy values .Finally, the proposed fuzzy logic method produced more than 85 %accurate results and error rate is very less compared to existing sentiment classification techniques.
关键词：Sentiment classification; Fuzzy logic; Fuzzy rules; Fuzzy C-means algorithm; Text mining