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Monetising User Generated Content Using Data Mining Techniques

Liu, Y., Ren, Y. and Dew, R.

    Social media systems such as YouTube are gaining phenomenal popularity. As they face increasing pressure and difficulties monetising the large amount of user-generated content, there are intense interests in technologies capable of delivering revenue to the owners. In this paper, we propose to use data mining techniques to help companies increase their revenue stream. Our approach differs principally in the underlying monetisation model and hence, the algorithms and data utilised. Our new model assumes both consumer and commercial content being entirely user-generated. We first present an algorithm to demonstrate one of possible monetisation technique that could be used in social media systems such as YouTube. A large volume of real-data harvested from YouTube will also be discussed and made available for the community to potentially kick start research in this direction.
Cite as: Liu, Y., Ren, Y. and Dew, R. (2009). Monetising User Generated Content Using Data Mining Techniques. In Proc. Australasian Data Mining Conference (AusDM'09) Melbourne, Australia. CRPIT, 101. Kennedy P. J., Ong K. and Christen P. Eds., ACS. 75-82
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