Interest point recommendation method and system based on co-occurrence graph

Abstract

The invention discloses an interest point recommendation method and system based on a co-occurrence graph. The recommendation method includes the five processes of data collection and processing, co-occurrence graph establishment, similarity calculation, position factor modeling and user recommendation. The interest point recommendation method based on the co-occurrence graph is characterized in that the co-occurrence graph between interest points is established through attendance data of users, two types of similarity between nodes is calculated based on the co-occurrence graph, and then the users are subjected to interest point recommendation according to the similarity between the nodes in the graph. Recommendation is carried out based on the novel perspective, namely the similarity between the interest points, and by means of the recommendation method, information in existing data is fully mined, and the problems of sparsity in the recommendation process of the interest points and scalability of recommendation methods in a large-scale social network are solved.

Description

technical field [0001] The invention belongs to the technical field of data mining and recommendation, and more specifically relates to a method and system for recommending points of interest based on co-occurrence graphs in a location social network. Background technique [0002] Point of interest (POI) recommendation originated from the development of location-based mobile Internet. POI recommendation is based on existing data to recommend locations that users may be interested in. POI recommendation service has great benefits for users and merchants in location-based social network (Location-based Social Network, LBSN). Accurate recommendation methods can greatly save users' time and improve user experience; at the same time, merchants Potential customers can be found through the recommender system. The above reasons make the POI recommendation problem an important research problem in industry and academia. [0003] POI recommendation is different from traditional recom...

AI Technical Summary

Problems solved by technology

[0005] In view of the above defects and improvement needs of the prior art, the purpose of the present invention is to provide a method and system for recommending points of interest based on co-oc

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