Department of Computer Science
Online discussion participation prediction using non-negative matrix factorization
This paper studies the online discussion participation prediction (OFPP). Online discussion is an application on the Web that provides a cyberspace for users to exchange or share different information. Finding suitable online discussions on Internet becomes difficult as huge amount of information existed. This led to recommendation systems that provide advices to users. In this paper, a weighted non-negative matrix factorization method is used to discover latent user preferences of online discussions such that prediction of user's participation can be obtained. Experimental results show that with the prediction of user's preferences, suitable online discussions can be suggested to the user.
Motion pictures, Online Communities/Technical Collaboration, Frequency, Intelligent agent, Internet, Information filtering, Information filters, Social network services, Conferences, Computer science, WNMFonline forumparticipation
Source Publication Title
Proceedings of the IEEE/WIC/ACM International Conferences on Intelligent Agent Technology: WI-IAT Workshops 2007) : 2-5 November, 2007, Silicon Valley, USA
Silicon Valley, United States
Copyright © 2007 by The Institute of Electrical and Electronics Engineers, Inc.
Link to Publisher's Edition
Fung, Yik-Hing, Chun-Hung Li, and William K. Cheung. "Online discussion participation prediction using non-negative matrix factorization." Proceedings of the IEEE/WIC/ACM International Conferences on Intelligent Agent Technology: WI-IAT Workshops 2007) : 2-5 November, 2007, Silicon Valley, USA (2007): 284-287.