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Analysis Study on Data Classification and Ranking for Sentimental Analysis in Data Mining
Abstract
Sentiment Analysis (SA) performs on specific domain to achieve higher level of accuracy. Extracting the unstructured data sentimental analyses plays a major role. SA is mainly for automatically predict sentiment polarity of positive or negative aspects of data. Sentiment Analysis problem is machine learning problems which provide the outcome based of supervised and unsupervised methods using labeled and unlabeled data. By extracting the data from this cross domain many techniques were used. This paper provides survey on sentiment analysis of various techniques, methods, algorithm and tools of SA to adapt the data in source and target domain to extract the relevant knowledge.
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