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THE PRIVATE RECOMMENDATION BASED ON THE ANALYSIS OF USER DYNAMIC BEHAVIOR

机译:基于用户动态行为分析的私人建议

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The traditional private recommendation system always ignores user dynamic behaviors. In consideration of the problem, the private recommendation based on the analysis of user dynamic behavior is provoked. This method recommends interested users in their virtual communities which are identified in the dynamic behavior network. The dynamic behavior network is built and made up of micro blog hot topics, users and participation behavior relationships. Meanwhile, this method not only considers the short-term dynamic interest, but also takes long-term stability interest into account. In order to get the weighted similarity of interest, establish the long-term interest model and short-term interest model, and trade off their contribution rate. Finally, experiment is done on a micro blog data set, The results show that this method has good effect.
机译:传统的私人推荐系统始终忽略用户动态行为。 考虑到问题,激发了基于用户动态行为分析的私人推荐。 此方法推荐在其虚拟行为网络中标识的虚拟社区中感兴趣的用户。 动态行为网络是由Micro Blog热门话题,用户和参与行为关系构建的。 同时,这种方法不仅考虑了短期动态兴趣,而且还考虑了长期稳定性的兴趣。 为了获得兴趣的加权相似性,建立长期利息模型和短期利息模型,并履行其贡献率。 最后,实验在微博数据集上完成,结果表明该方法具有良好的效果。

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