Computer Science ›› 2016, Vol. 43 ›› Issue (4): 7-15.doi: 10.11896/j.issn.1002-137X.2016.04.002

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Research Status and Future Trends of Recommender Systems for Implicit Feedback

LU Yi and CAO Jian   

  • Online:2018-12-01 Published:2018-12-01

Abstract: As an effective approach addressing information overloading problem,recommender system has been a hot-spot in both industry and academia,which infers users’ potential requirements and interests by utilizing their explicit/implicit feedbacks,and then recommends them with preferable information or products.The recommendation methods based on explicit feedbacks are the mainstream approaches in this area,however,because of the prevalence of implicit feedbacks,the recommendation methods for implicit feedbacks can be more widely applied.Because the implicit feedbacks cannot reflect users’ preferences directly,to recommend products relying on implicit feedbacks is a more challen-ging task.The characteristics of implicit feedback,necessity and problems of recommendation for implicit feedbacks were illustrated firstly.Then a systematic taxonomy for various recommendation methods on implicit feedback was proposed.On this basis,the strength/weakness of these approaches and evaluation metrics for implicit feedback oriented recommendation were analyzed.Lastly,the possible directions of implicit feedback oriented recommendation in the future were discussed.

Key words: Recommendation algorithms,Implicit feedback,Recommendation evaluation metrics

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