Behavior prediction method and device based on behavior co-occurrence network, equipment and medium

Abstract

The invention relates to the field of artificial intelligence, and provides a behavior prediction method and device based on behavior co-occurrence network, equipment and a medium, which can obtain behavior information of a target user, and divide behaviors of the target user into at least one behavior segment according to occurrence time of each behavior so as to distinguish the behaviors of theuser. Different action subjects are effectively decoupled, behavior information of a user is better learned, a target behavior co-occurrence network is constructed based on behavior segments and inputinto a pre-constructed behavior prediction model, a prediction result is output, and the behavior prediction model is obtained based on Graph Pooling and co-occurrence network training. The behaviorco-occurrence relation is constructed through the divided behavior segments, the target behavior co-occurrence network is constructed, the distinction degree between the behavior segments is enhanced,model prediction is more accurate, and then behavior prediction of the user is achieved based on an artificial intelligence means. The invention also relates to a blockchain technology, and the behavior prediction model and the prediction result can be stored in the blockchain.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a behavior prediction method, device, equipment and medium based on a behavior co-occurrence network. Background technique [0002] The behavior sequence modeling method adopted in the prior art generally expresses user behavior information as a sequence, and performs modeling based on the sequence model, expresses behaviors such as clicks as a discrete and continuous sequence, and then intercepts the most recent period of time. Behavior or several recent behavior actions, let the model learn the user's behavior information. [0003] However, even for the click behavior of the same user, because the user may do different things at different times, if the behavior segment is not distinguished, it will cause a variety of heterogeneous information to be coupled together, making it difficult to distinguish. The subject of behavior is unclear, which further le...

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Problems solved by technology

[0003] However, even for the click behavior of the same user, because the user may do different things at different times, if the behavior segment is not distinguished, it will cause a variety of heterogeneous information to be coupled together, making it difficult to distinguish. The subject of the behavior is unclear, which further leads to insufficient prediction accuracy of the model

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