Behavior perception recommendation method, terminal and computer readable storage medium

Abstract

The invention discloses a behavior perception recommendation method, a terminal and a computer readable storage medium, and the method comprises the steps: obtaining attention scores of a next behavior and a current behavior of a target object, and adding the attention scores as heterogeneous behavior information into an input layer of a perception recommendation model; introducing a target behavior at the output side of the perception recommendation model, and training the perception recommendation model according to the target behavior to obtain a trained perception recommendation model; and predicting a target behavior of the target object according to the trained perception recommendation model to obtain a next behavior prediction result corresponding to the target behavior, and recommending the obtained prediction result to a client where the target object is located. According to the method, the attention mechanism is applied to the input layer, and the attention score between the next behavior and the current behavior is used as heterogeneous behavior information, so that the problem that the isomerism cannot be distinguished is solved; meanwhile, a real next behavior is introduced to the output side, so that the problem of inaccurate isomerism prediction is solved.

Description

technical field [0001] The present invention relates to the field of data mining applications, in particular to a behavior-aware recommendation method, a terminal and a computer-readable storage medium. Background technique [0002] The recommendation system has become an indispensable part of today's Internet. It is widely used in major website platforms, which can greatly alleviate the problem of information overload and realize personalized recommendation. Existing recommendation algorithms recommend to a user items that he / she may be interested in in the future based on the user's historical interaction records. The sequence recommendation algorithm is a research hotspot in the recommendation algorithm. It recommends the user's next interaction by considering the user's historical interaction sequence in chronological order, which is in line with our real application scenario. Most sequence recommendation algorithms only recommend for a single type of interaction sequen...

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is that, aiming at the defects of the existing technology, the present invention provides a behavior-aware recommendation method, a terminal and a computer-readable storage medium to solve the existing technical problem of inaccurate heterogeneous prediction

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