Cold-start eliminating method of collaborative filtering based on n-sequence access analytic logic
Cong Li · Systems Engineering - Theory & Practice · 2012
Collaborative filtering is the most successful and widely used recommendation technology in personalized recommender systems.However,collaborative filtering faces cold-start problem,which includes new user problem and new item problem,when user ratings are extremely sparse.To solve the new user problem,a cold-start eliminating method was proposed.Firstly,the items access by user was obtained via web logs;secondly,n-sequence access analytic logic was defined to decompose user's access item sequence to user access sub-sequence set;thirdly,a similarity measure for user access item sequence was proposed to search target user's nearest neighborhood;fourthly,improved most-frequent item extracting algorithm,which called IMIEA,was proposed to obtain the top-N recommendation for the new user.The experimental results show that the proposed method can efficiently eliminate new user problem and obtain better top-iV recommendation quality.