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Who Resemble You Better, Your Friends or Co-visited Users

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7235))

Abstract

People are alike their graphic neighbors in social networks, which is generally accepted as the basic assumption in interest prediction. But what kind of neighbors is a better information source? This paper aims at answering this question by comparing the results of predicting users’ interests in blog social networks with different relationships and parameters. Since social networks usually keep “friends” and “visitors” as basic social roles, we take these two online social relationships as the main information source. In this paper, we discover that (1) combining different information sources might lead to better prediction, and (2) there are many other factors that can affect the results significantly.

This work was supported by NSFC with Grant No. 61073081 and 60933004, and HGJ 2010 Grant 2011ZX01042-001-001.

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© 2012 Springer-Verlag Berlin Heidelberg

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Ma, J., Zhang, Y. (2012). Who Resemble You Better, Your Friends or Co-visited Users. In: Sheng, Q.Z., Wang, G., Jensen, C.S., Xu, G. (eds) Web Technologies and Applications. APWeb 2012. Lecture Notes in Computer Science, vol 7235. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29253-8_52

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  • DOI: https://doi.org/10.1007/978-3-642-29253-8_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29252-1

  • Online ISBN: 978-3-642-29253-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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