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What is Maximum Entropy Classifier

Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence
This classifier determine the most likely class for a document set it convert the labelled document set into a vector using encoding and with the help of encoded vector we calculate the weight of a document and combine to get the result.
Published in Chapter:
Aspect-Based Sentiment Analysis of Online Product Reviews
Vinod Kumar Mishra (Bipin Tripathi Kumaon Institute of Technology, India) and Himanshu Tiruwa (Bipin Tripathi Kumaon Institute of Technology, India)
DOI: 10.4018/978-1-5225-2031-3.ch010
Abstract
Sentiment analysis is a part of computational linguistics concerned with extracting sentiment and emotion from text. It is also considered as a task of natural language processing and data mining. Sentiment analysis mainly concentrate on identifying whether a given text is subjective or objective and if it is subjective, then whether it is negative, positive or neutral. This chapter provide an overview of aspect based sentiment analysis with current and future trend of research on aspect based sentiment analysis. This chapter also provide a aspect based sentiment analysis of online customer reviews of Nokia 6600. To perform aspect based classification we are using lexical approach on eclipse platform which classify the review as a positive, negative or neutral on the basis of features of product. The Sentiwordnet is used as a lexical resource to calculate the overall sentiment score of each sentence, pos tagger is used for part of speech tagging, frequency based method is used for extraction of the aspects/features and used negation handling for improving the accuracy of the system.
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