The Recommendation System Based On Two-sides Selection Between College Graduates And Employers

The emergence of recommendation system provided powerful technical support for solving the problem of information overload in the era of big data.Personalization recommendation technology has been successfully applied in Electronic Commerce and rich results had been obtained.The research and application of personalization recommendation technology was still in the further research and exploration in the field of employment of college graduates.Faced with the increasingly serious problem of employment of college graduates,the recommendation system based on two-sides selection between college graduates and employers was studied and designed.Firstly,the background of the research and the current research situation at home and abroad were summed up.Secondly,the key technology of recommendation system were introduced,the common recommendation algorithm and recommendation system evaluation index were analysised.Then the characteristics of the network recruitment system were analysised.There were two kinds of peer to peer users in this field.In order to solve the problems such as cold start and data sparsity,the recommendation algorithm was used based on content filtering and the collaborative filtering recommendation algorithm based on double clustering,the two recommendation algorithms were fused as the system's recommendation engine.Finally,the employment recommendation system was designed and implemented.The result of experiments show that the hybrid recommendation system can effectively make use of the advantages of the two kinds of recommendation algorithms,achieving better recommendation results.