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- W2370251566 abstract "An important facet of Last.FM and MovieLens is that users manually annotate the items using so called tags.There are many researches about using tag to improve the quality of recommendation.However,tags are local descriptions of items given by the users,because different people use different tags for the same item,but the tags may represent the same means.In this paper,we used tag grouping method to group the tag according to the similarity of co-occurrence distributions.Based on this,we proposed an approach to group synonymy tags and fusing the relationship between users-tag with the collaboration filtering algorithms.The results of the empirical evaluation show that the approach is effectiveness in augmenting recommendation." @default.
- W2370251566 created "2016-06-24" @default.
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- W2370251566 date "2011-01-01" @default.
- W2370251566 modified "2023-09-25" @default.
- W2370251566 title "Collaborative Recommendation Based on Synonymy Tags Grouping" @default.
- W2370251566 hasPublicationYear "2011" @default.
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