earticle

영어

To ameliorate the limitations of traditional collaborative filtering technologies and enhance the recommendation quality of agricultural science and technology information, a collaborative filtering recommendation method based on synthetic strategy is proposed. Firstly, filter the user set and user-item rating matrix according to the location of target user, which can solve the regional problem. Then, predict ratings of items according to the similarity of users or item content, which can relax the impact of the sparse rating. In addition, add the rating time to the user-item rating matrix to distinguish the timeliness of the user preference, and add user preference shifting in the similarity formula as a factor which can express the similarity of users or item content better. Our method can not only guarantee the recommended information is local and suit to current season of agricultural production, but also ensure the recommending precision under sparse rating data.