Gowtamreddy, P (2014) Opinion mining of online customer reviews. MTech thesis.
Customer Opinions play a very crucial role in daily life. When we have to take a decision, opinions of other individuals are also considered. Now-a-days many of web users post their opinions for many products through blogs, review sites and social networking sites. Business organizations and corporate organizations are always eager to find consumer or individual views regarding their products, support and service. In e-commerce, online shopping and online tourism, its very crucial to analyse the good amount of social data present on the Web automatically therefore, its very important to create methods that automatically classify them. Opinion Mining sometimes called as Sentiment Classification is defined as mining and analysing of reviews, views, emotions and opinions automatically from text, big data and speech by means of various methods. In this thesis we are going to see how Apriori frequent item set mining algorithm can be used for mining reviews from online reviews those are posted by customers. Our main theme is to create a system for analysing opinions which implies judgement of different consumer products.
|Item Type:||Thesis (MTech)|
|Uncontrolled Keywords:||Opinion Mining; Sentiment Classification; Apriori Algorithm; SentiWordNet; Min-max Normalization; Frequent Words; Online Reviews|
|Subjects:||Engineering and Technology > Computer and Information Science > Data Mining|
|Divisions:||Engineering and Technology > Department of Computer Science|
|Deposited By:||Hemanta Biswal|
|Deposited On:||08 Sep 2014 11:14|
|Last Modified:||08 Sep 2014 11:14|
|Supervisor(s):||Babu, K S|
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