Online rating system is a popular feature of Web 2.0 applications. It typically involves a set of reviewers assigning rating scores (based on various evaluation criteria) to a set of objects. We identify two objectives for research on online rating data, namely achieving effective evaluation of objects and learning behaviors of reviewers/objects. These two objectives have conventionally been pursued separately. We argue that the future research direction should focus on the integration of these two objectives, as well as the integration between rating data and other types of data.
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
National Science Foundation Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation NGDM 2007, October 10-12
City or Country
LAUW, Hady Wirawan and LIM, Ee Peng.
A Multitude of Opinions: Mining Online Rating Data. (2007). National Science Foundation Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation NGDM 2007, October 10-12. 1-5. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1262
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