Recommendation method based on user character label

Abstract

The invention discloses a recommendation method based on a user personality label. Development of a user behavior index list, modeling of a user personality-recommendation mode matching rule, development of a recommendation mode list, development of the user personality label, modeling of user online behavior indexes and the like are achieved. According to the invention, a psychological charactertheory is used as a basis; data such as use behaviors and comments of the user on the product are comprehensively analyzed by utilizing a big data technology; according to the method, the personalityof the user is mined, the user behavior model is constructed, a user personality label and a corresponding recommendation mode are developed, related recommendation can be carried out on the user according to a specific application scene, and the method is suitable for recommendation systems of platforms such as e-commerce and social networks. Due to the fact that the internal stability, interpretability and mobility of user characters are high, the cold start problems that system data are sparse and cannot be migrated, and the new user recommendation effect is poor can be effectively solved by utilizing character labels to recommend.

Description

technical field [0001] The invention belongs to the technical field of big data processing, and in particular relates to a recommendation method based on user personality tags. Background technique [0002] With the advent of the era of big data, the amount of information in the network has shown exponential growth, and a large amount of redundant information has seriously interfered with the accuracy of Internet users' selection of relevant and useful information, and recommendation systems have emerged as the times require. The recommendation system can analyze and find information that users may be interested in from a large amount of information according to different algorithm models, so as to recommend items to users that they may like now or in the future. [0003] At present, recommendation systems are mostly used in e-commerce shopping websites, social networking, and information network information platforms to recommend related products and projects. Collaborativ...

AI Technical Summary

Problems solved by technology

However, in this type of research, the measurement of personality is carried out through questionnaires and self-subjective feedback by users. The measurement efficiency is low and stays on the surface, and it cannot essentially reflect the role of personality in the recommendation system.

[0005] Recommendation systems generally use labels combined with different recommendation methods to implement the recommendation process, which requires continuous development of labels. The unstable nature of labels will lead to inaccurate recommendation systems using such labels and cannot meet the recommendation needs of users.

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