Individual recommendation method and device based on fusion strategy

Abstract

The invention discloses an individual recommendation method and a device based on fusion strategy. The individual recommendation method comprises the following steps: respectively confirming a first score value obtained by using a collaborative filtering recommendation method based on users, of a target user on a target item, confirming a second score value obtained by using a recommendation method based on image similarity, of the target user on the target item, and subsequently adding the weights of the first score value and the second score value so as to confirm a final score value of the target user on the target item, that is, the score values predicted by using the two methods are comprehensively considered. Therefore, the problems that a single recommendation algorithm is low in recommendation quality and the reliability is low are solved.

Description

technical field

[0001] The present application relates to the technical field of collaborative recommendation, and more specifically, to a personalized recommendation method and device based on a fusion strategy. Background technique

[0002] With the development of e-commerce, the proportion of images used in online shopping malls continues to expand. According to statistics, the proportion of images in visual information has exceeded 25%. The amount of data-rich information contained in images plays a vital role in the user's shopping experience. Therefore, how to effectively use these image information to quickly and efficiently recommend products to users is a problem worthy of research and solution.

[0003] Traditional methods include user-based collaborative filtering methods and image similarity-based recommendation methods. Among them, when the former predicts a certain user's preference for a certain visual product, it predicts the user's preference by judging th...

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