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Multi-Objective Sentiment Analysis Using evolutionary algorithm for Mining Positive & Negative Association Rules Swati V. Gupta1, Madhuri S. Joshi2 1,2 Department of Computer Science & Engineering, MGM s Jawaharlal Nehru Engineering College, N-6 CIDCO, Aurangabad - 431003, M. S., India Abstract- Most of the algorithms for mining Quantitative Association Rules (QAR) focuses on positive dependencies without paying particular attention to negative dependencies. The latter may be worth taking into account, however, as they relate the presence of certain items to the absence of others. The algorithms used to extract such rules usually consider only one evaluation criterion in measuring the quality of generated rules. Recently, some researchers have framed the process of extracting association rules as a multiobjective problem, allowing us to jointly optimize several measures that can present different degrees of tradeoff depending on the dataset used.
Multi-Objective Sentiment Analysis Using Evolutionary Algorithm for Mining Positive & Negative Association Rules Swati V. Gupta1, Madhuri S. Joshi2 1,2 Department of Computer Science & Engineering, MGM’s Jawaharlal Nehru Engineering College,
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