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

A technology of linked data and recommendation system, which is applied in the field of data security, can solve the problems of large amount of calculation and cannot be applied to the recommendation environment, and achieve the effect of avoiding the problem of large data volume and improving accuracy

Active Publication Date: 2021-09-24
GUANGXI NORMAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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

Method used

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

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Embodiment Construction

[0035] In the present invention, according to the difference of the applicable recommendation system, the items that the user pays attention to (that is, recommends) will also be different. If it is a recommendation system for commodity trading, the item (recommendation) concerned is the product purchased, such as Taobao, Jingdong, Amazon or Meituan, etc.; if it is a recommendation system for tourism, the item (recommendation) concerned is travel Attractions, such as Baidu Travel, Mafengwo, Qyer.com or Lvmama, etc.; if it is a recommendation system for job hunting, the item (recommendation) concerned is work, such as Zhaopin, 51job, or ChinaHR; if it is a document A recommendation system like this, the items (recommendations) concerned are articles, such as CNKI, Baidu Academic or Wanfang Data knowledge service platform and so on.

[0036] In this embodiment, the transaction recommendation system is taken as an example to illustrate the present invention, see figure 1 , an an...

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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...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9535G06Q50/00
CPCG06Q50/01G06F16/9535
Inventor 王利娥李先贤程民权刘鹏
Owner GUANGXI NORMAL UNIV
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