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Issue No.03 - May-June (2013 vol.17)
pp: 76-79
Qin Lv , University of Colorado Boulder
ABSTRACT
Randomly pairing up strangers in online video chat services has quickly gained popularity over the past few years. One major issue that has emerged is the existence of misbehaviors and obscene content. Detecting misbehavior in online video chat services requires effective fusion of multiple types of evidence as well as efficient fusion strategies.
INDEX TERMS
Information filtering, Internet, Online services, Video communication, Legal aspects, data fusion, online video chat, misbehavior
CITATION
Qin Lv, "Detecting Misbehavior in Online Video Chat Services", IEEE Internet Computing, vol.17, no. 3, pp. 76-79, May-June 2013, doi:10.1109/MIC.2013.47
REFERENCES
1. X. Xing et al., "SafeVchat: Detecting Obscene Content and Misbehaving Users in Online Video Chat Services," Proc. 20th Int'l Conf. World Wide Web, ACM, 2011, pp. 685–694.
2. H. Cheng et al., "Efficient Misbehaving User Detection in Online Video Chat Services," Proc. 5th ACM Int'l Conf. Web Search and Data Mining, ACM, 2012, pp. 23–32.
3. X. Xing et al., "Scalable Misbehavior Detection in Online Video Chat Services," Proc. 18th ACM SIGKDD Conf. Knowledge Discovery and Data Mining, ACM, 2012, pp. 552–560.
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