Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 462-467.

• Big Data & Data Mining • Previous Articles     Next Articles

Research on News Recommendation Methods Considering Geographical Location of News

YUAN Ren-jin, CHEN Gang   

  1. Institute of Geospatial Information,Information Engineering University,Zhengzhou 450052,China
  • Online:2019-02-26 Published:2019-02-26

Abstract: In order to research the impact of news event place on the recommendation performance of news recommendation system,a News recommendation algorithm Considering Geographical Position(NCGP) method is proposed.Firstly,an algorithm was designed to extract the place of news event.Secondly,the vector space model,TF-IDF algorithm and word2vec tool were used to construct the news feature vector.Then,constructing the user interest model was discussed deeply.Finally,the cosine similarity method was used to calculate the similarity between the user interest model and the candidate news set to complete the recommendation.The experimental results show that the performance of the proposed news event place extraction algorithm is better,and the precision can reach 93.6%,besides,the F-value of NCGP is improved compared with the collaborative filtering recommendation algorithm and the recommendation algorithm that only considers news content.

Key words: Recommendation system, Geographical location, User interest model, Information extraction, Vector space model

CLC Number: 

  • TP391
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