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Security cross-domain recommendation method based on multi-feature collaborative knowledge graph and block chain

A knowledge map and recommendation method technology, applied in the field of safe cross-domain recommendation, can solve the problem of low recommendation accuracy and achieve the effect of improving recommendation accuracy, protecting privacy and security, and accurate win-win recommendation effect

Pending Publication Date: 2021-11-23
GUANGXI NORMAL UNIV
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AI Technical Summary

Problems solved by technology

However, with the rapid growth of the user scale and the number of items, the existing recommendation methods have low recommendation accuracy

Method used

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  • Security cross-domain recommendation method based on multi-feature collaborative knowledge graph and block chain
  • Security cross-domain recommendation method based on multi-feature collaborative knowledge graph and block chain
  • Security cross-domain recommendation method based on multi-feature collaborative knowledge graph and block chain

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Embodiment Construction

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention.

[0025] Now the most widely used collaborative filtering recommendation algorithm has a serious problem of data sparsity. Due to the lack of enough data to construct accurate user portraits, the recommendation results are biased and the quality of the recommendation is greatly reduced. The cross-domain recommendation technology that integrates auxiliary data can effectively improve the recommendation accuracy in the case of sparse data. The essence of cross-domain recommendation is to use the correlation between auxiliary domain data and target domain data to obtain effective user preferences or item characteristics. information to enrich target user data. Based on multi-dimensional data from different sources, more accurate user portraits can be constructed, thereby overcoming ...

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Abstract

The invention relates to the technical field of data processing, in particular to a security cross-domain recommendation method based on a multi-feature collaborative knowledge graph and a block chain. The method comprises the steps that a client stores user data which is not uploaded to a server, and uploads the user data after preprocessing the user data; a multi-feature collaborative knowledge graph is constructed to perform cross-domain information security fusion; all participants register and join the block chain, and write an operation upper chain so as to carry out data anomaly detection analysis and source tracing; and the user characteristics and the knowledge graph are taken as input of a GCN, and a personalized recommendation list is output to a target user. Features are used as entity nodes in the knowledge graph to hide sensitive information associated with individuals, and privacy security is protected while user data analysis requirements in recommendation are met; for model poisoning attacks, a block chain technology is introduced to realize traceability of upper chain data, and the security of the data is ensured from the source; and the correctness and integrity of the collected data are realized, so that the recommendation accuracy is improved.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a safe cross-domain recommendation method based on a multi-feature collaborative knowledge graph and a blockchain. Background technique [0002] As a data screening tool that can effectively cope with the explosive growth of information, the recommendation system is essentially to construct user portraits based on user historical data, and actively recommend objects that are consistent with user preferences. The objects can be not only commodities, but also services, such as Various leisure and entertainment services such as travel services, ticketing services, and meal ordering services provided by certain businesses. However, with the rapid increase of the user scale and the number of items, the existing recommendation methods have low recommendation accuracy. Contents of the invention [0003] The purpose of the present invention is to provide a safe cross-domain re...

Claims

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Application Information

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IPC IPC(8): G06F16/36G06F16/9535G06F16/9536G06F21/62G06N3/04G06N3/08
CPCG06F16/367G06F16/9535G06F16/9536G06F21/6245G06N3/08G06N3/045
Inventor 王利娥李先贤柒月兰李东城
Owner GUANGXI NORMAL UNIV
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