Intelligent recommendation method based on physical environment, a system and a storage medium thereof

Abstract

The invention discloses an intelligent recommendation method based on physical environment, a system and a storage medium thereof. The method comprises the following steps: S1, when a user needs recommendation, a user terminal obtains current environmental information through a physical environment sensing module and obtains the geographical position of the user by combining LBS technology; 2, theuser terminal obtains the current environmental information through a physical environment sensing module. 2, that user terminal is communicatively connected with the cloud server, and the cloud server obtains the user data of the us and establishes a user interest model for the user; S3: The physical environment data of the user, The user portrait data, LBS data and recommendation data are inputted into the user interest model, and the user interest model is processed by the cloud server through the depth learning technology and natural language technology, and the operation result is returned to the user terminal, so that the user can obtain the personalized intelligent recommendation content. The invention solves the problem that the terminal recommendation content is single, and can carry out accurate personalized intelligent recommendation according to the current physical environment of the user, thereby increasing the user experience.

Description

technical field [0001] The invention relates to the field of the Internet, in particular to an intelligent recommendation method based on a physical environment, a system and a storage medium thereof. Background technique [0002] The online recommendation method can obtain the user's interest preference from the interaction data with the user while making the recommendation, and adjust the recommendation strategy in real time to adapt to the user's interest preference. In each recommendation round, the recommendation method first observes the characteristics of the user and all candidate items, then decides the recommended item according to the recommendation strategy, and finally updates the recommendation strategy according to the actual item selected by the user. With the rapid growth of observable data and the substantial improvement of hardware computing power, online recommendation methods have been widely used in the fields of economy, education, games and multimedia...

AI Technical Summary

Problems solved by technology

[0006] In order to meet the above requirements, an object of the present invention is to provide an intelligent recommendation method based on the physical environment. Accurate and personalized intelligent recommendations for various content, increasing user experience

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