Opinion Extraction & Classification of Reviews from Web Documents
Shishir Kumar Shandilya, Suresh Jain · 2009
Automatic extraction of opinions on products from Web has been receiving interest increasingly. Such extracted knowledge helps to find out what other people think about the particular product or service. With the growing availability of resources like online review sites and personal blogs, new opportunities and challenges arise as people can, and do, actively use information technologies to seek out and understand the opinions of others. The sudden growth in the area of opinion mining, which deals with the computational techniques for opinion extraction and understanding created an utmost need to understand and view the Web in a different prospect. In this paper, we demonstrate an opinion-mining framework that extracts the opinions and views of the consumers/customers, and analyze them to provide concrete market flow along with proven statistical data. The software uses classification, clustering and lingual knowledge-based opinion mining for providing these features.