Publication Type

Conference Paper

Publication Date

10-2007

Abstract

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.

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

National Science Foundation Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation NGDM 2007, October 10-12

First Page

1

Last Page

5

City or Country

Baltimore, MD

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://www.csee.umbc.edu/~hillol/NGDM07/abstracts/poster/HLauw.pdf

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