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User Clustering Topic Recommendation Algorithm based on Two Phase in the Social Network

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成果类型:
会议论文
作者:
Shu LI
作者机构:
[Shu LI] Hunan City University
语种:
中文
关键词:
Collaborative filtering;Clustering;Data set;Fuzzy Degree
年:
2017
页码:
5-11
会议论文集名称:
International Journal of Intelligent Information and Management Science(Volume 6, Issue 3, June 2017)
会议时间:
2017-06
基金类别:
supported by the Hunan Science and Technology Project (No. 2012FJ6011);the Construct Program of the Key Discipline in Hunan Province, China
机构署名:
本校为第一机构
摘要:
To deal with the issues like existing common data sparseness in weibo social network and the phenomena of cold start, this paper puts forward a two-stage clustering based on the recommendation algorithm GCCR. The algorithm firstly selects users’ focused nodes which have higher number, so as to extract a dense subset of sparse data, and by using the method of graph paper, similar concerned interested core clustering is formed to this dense subset. Then, it is extracted that weibo content features of seed clustering and the whole data set other ...

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