Computer Science ›› 2018, Vol. 45 ›› Issue (9): 253-259.doi: 10.11896/j.issn.1002-137X.2018.09.042

• Artificial Intelligence • Previous Articles     Next Articles

Real-time Personalized Micro-blog Recommendation System

LIU Hui-ting, CHENG Lei, GUO Xiao-xue, ZHAO Peng   

  1. School of Computer Science and Technology,Anhui University,Hefei 230601,China
  • Received:2017-08-29 Online:2018-09-20 Published:2018-10-10

Abstract: At present,many social networking services do not fully consider the personalized needs of users,and it is difficult to guarantee the real-time services because social networking services need to deal with massive amounts of data.A micro-blog recommendation model called RPMPS based on LDA topic model and KL divergence was proposed to respond to users’ personalized request in micro-blog recommendation in real time and improve the efficiency and quality of recommendation.RPMPS model not only uses the document-topic probability distribution matrix to get the similarity between the topic of user information and the topic of candidate micro-blog,but also obtains the similarity between the content of user information and the content of candidate micro-blog by utilizing the document-word to count the probability of the word frequency .At last,the real-time personalized micro-blog recommendation system based on RPMPS model is constructed,and micro-blog is filtered during the course of data processing to shorten the system response time.Experimental results on real-world datasets demonstrate that the system can meet the real-time personalized demands of users.

Key words: Micro-blog, Recommendation system, RPMPS recommendation model, Social network

CLC Number: 

  • TP319
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