E-commerce web has evolved as a key source of unstructured data rich in customer opinion. Understanding user reviews and mining opinion is an important research area in computer science which mostly relies on statistical inference methods. A deterministic and efficient algorithm to mine opinion remains far in the future. In this paper, domain specific strategies for optimizing existing product rating methods are discussed. The proposed strategies include a simple method to filter out irrelevant words from extracted nouns, an application of improved apriori algorithm and a new mathematical estimation of the overall rating. These methods can improve the efficiency in terms of running time of algorithms and accuracy of results. An empirical analysis of accuracy and efficiency of our methods is also presented.
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P. R. Sharma, Yathu, E. M., and Jayakumar P., “Optimization Strategies for Product Rating Using User Review Analysis”, International conference on computing paradigms(ICCP 2016), International Journal of Control Theory and Applications . pp. 4553-4562, 2016.