出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Text is the main method of communicating information in the digital age. Messages, blogs,news articles, reviews, and opinionated information abounds on the Internet. People commonlypurchase products online and post their opinions about purchased items. This feedback isdisplayed publicly to assist others with their purchasing decisions, creating the need for amechanism with which to extract and summarize useful information for enhancing the decisionmakingprocess. Our contribution is to improve the accuracy of extraction by combiningdifferent techniques from three major areas, namedData Mining, Natural Language Processingtechniques and Ontologies. The proposed framework sequentially mines product’s aspects andusers’ opinions, groups representative aspects by similarity, and generates an output summary.This paper focuses on the task of extracting product aspects and users’ opinions by extractingall possible aspects and opinions from reviews using natural language, ontology, and frequent“tag”sets. The proposed framework, when compared with an existing baseline model, yieldedpromising results.
