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Abstract User preference mining is one of the key problems in personalized recommendations and intelligent services. Social tagging in web2.0 reflects the user's potential interests. This paper presents a user preference modeling method based on social tagging that predicts user preferences based on interactions between user and tag. The user's “degree of recognition” and “dependency” on an individual tag are combined to evaluate the user's tag preference. The user's interest is then decomposed into a fine-grained result using a “Tag Genome”. Tests based on real data demonstrate that this method significantly improves prediction accuracies and coverage to more accurately match the user's real interests.
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| Keywords
user model
social tags
data mining
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Issue Date: 15 April 2014
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2014,
Vol. 54
),Yuezhi ZHOU
