User reviews data analysis using opinion mining on web

The web world is thriving with e-commerce these days and the need for online reviews has become crucial. The product reviews guide the customers and help them in making decisions regarding various available products which otherwise would bemuse them. But, one issue hampering this decision making problem is to sift through the huge jumbled piles of reviews available on the vast web. This makes the automatic extraction, summarization, and tracking of the available opinions very beneficial for the customers looking to buy a product. The automatic summarization and classification is different for different domains and varies with the testing situations. Through this paper, we are discussing usefulness of mining the customer opinions (i.e. opinion mining) and experimenting its viability in the mobile domain. Our implementation in mobile domain will be based on three main steps: 1) Applying Part-of-speech Tagging (POST), 2) Rule-Mining and identifying opinion words, 3) Summarizing and displaying the end results.