Coding-based anonymous recommendation methods in recommender systems with linked data

Abstract

The invention discloses a code-based anonymous recommendation method in a recommendation system for associated data, which allows users to add long-term and short-term friends to build a circle of friends, so as to take into account the long-term and short-term interests of users; and build personalized item codes in the circle, and Generate a user feature code and send it to the recommendation center, and the recommendation center will perform calculations based on the feature code to obtain a synthetic recommendation. The purpose of the present invention is to fully consider the relationship between users and personal hobbies, localize the data in the form of friend circles to effectively avoid the problem of large data volume, allow friends to overlap to solve the problem of local project diversity, and use user characteristics In the form of code, an effective and accurate recommendation list can be obtained while protecting user privacy information.

Description

technical field [0001] The invention relates to the technical field of data security, in particular to an anonymous recommendation method based on coding in a recommendation system of associated data. Background technique [0002] In recent years, recommender systems have been widely used in many fields, such as e-commerce, social networks, personalized reading and advertising, location-based services and mobile recommendations, etc. The essence of the recommendation system is to analyze the collected data information to predict whether a given user will like a specific item. It can be seen that to achieve a good recommendation effect must come from rich and accurate data information (user information, preference information and project information, etc.). A recommendation system based on linked data can associate data from a variety of different data sources, conduct more in-depth analysis and pattern mining on user data information, and can realize cross-domain semantic r...

AI Technical Summary

Problems solved by technology

[0009] What the present invention aims to solve is the problem that the existing anonymous technology cannot be applied to the recommendation environment based on associated data due to the large amount of calculation, and provides an anonymous recommendation method based on encoding in the recommendation system of associated data

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