Micro-blog User Recommendation Based on User Profile

doi:10.3969/j.issn.1006-2475.2017.10.016

Abstract

Abstract: Using of single data source and the simple model in the traditional micro-blog recommendation results in the low recommendation accuracy. Therefore, a new recommendation algorithm based on labeled User Profile is proposed to overcome such issue. By analyzing the significance and correlation of individual user data, such as text, label, social relationship, and personal information, the algorithm generates new labels and suggests related interests by training LDA model and SVM classifier. The user’s interests are assigned by weighted sum of these factors. The overall recommendation accuracy is improved. The experiments show that the properties of the algorithm are better than the traditional VSM model, allowing users to have a better micro-blog experience.

Key words: micro-blog, label, User Profile, user recommendation

JIANG Zong-li， KANG Ya-ru. Micro-blog User Recommendation Based on User Profile[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.10.016.

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