Beyond the Stars: Improving Rating Predictions using Review Text Content

Online reviews are an important asset for users deciding to buy a product, see a movie, or go to a restaurant, as well as for businesses tracking user feedback. However, most reviews are written in a free-text format, and are therefore difficult for computer systems to understand, analyze, and aggregate. One consequence of this lack of structure is that searching text reviews is often frustrating for users. User experience would be greatly improved if the structure and sentiment conveyed in the content of the reviews were taken into account. Our work focuses on identifying this information from free-form text reviews, and using the knowledge to improve user experience in accessing reviews. Specifically, we focused on improving recommendation accuracy in a restaurant review scenario. In this paper, we report on our classification effort, and on the insight on user-reviewing behavior that we gained in the process. We propose new ad-hoc and regression-based recommendation measures, th...

• Type: Conference
• Year: 2009
• Where: WEBDB
• Authors: Gayatree Ganu, Noemie Elhadad, Amélie Marian
• Keywords: Internet Technology, Review, Text Reviews, User Experience, WEBDB 2009