Privacy protection mobile service recommendation method, client and recommendation system

A technology for privacy protection and service recommendation, which is applied in the field of privacy protection network service recommendation methods and recommendation systems, can solve the problems of incompatibility between user privacy protection and recommendation service quality, and achieve the effect of maintaining recommendation accuracy

Active Publication Date: 2019-10-11
HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem mainly solved by the present invention is how to overcome the problem that user privacy protection and recommended service quality cannot be balanced in the existing mobile service recommendation system

Method used

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  • Privacy protection mobile service recommendation method, client and recommendation system
  • Privacy protection mobile service recommendation method, client and recommendation system
  • Privacy protection mobile service recommendation method, client and recommendation system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] Please refer to figure 1 , the present application discloses a method for recommending privacy-protected mobile services, which mainly includes steps S100-S400, which will be described respectively below.

[0034] Step S100, namely the obtaining step, obtains sample data of the user, where the sample data is omission information, false information, coarse-grained information or fine-grained information of the user's personal information. In a specific example, see figure 2 , the step S100 may include steps S110-S180, which are respectively described as follows.

[0035] Step S110, collecting user's personal information. The user's personal information includes but is not limited to name, gender, age, country, language, sports hobbies, food hobbies, film and television hobbies, music hobbies, shopping interests, current geographical location, etc. The user's personal information can be preset in the user On the terminal device, it is enough to read the user's persona...

Embodiment 2

[0088] Please refer to Figure 4 , on the basis of the privacy protection mobile service recommendation method disclosed in Embodiment 1, this embodiment also discloses a recording step S500, which is located after step S400, which may include steps S510-S530, which will be described below.

[0089] Step S510, generating a click record in response to the user's click operation in the second service recommendation list, where the click record includes the access address of the clicked recommended item and the user's network identity information.

[0090]For example, after the user browses the second service recommendation list (such as a commodity purchase list) on the client device, he will often select a recommended item (such as one of the commodities) in the second service recommendation list to view, and at this time A click operation is generated through touch click, mouse click, gesture recognition, etc., then a click record will be generated, recording the access addres...

Embodiment 3

[0095] Please refer to Figure 5 , a privacy-protected client 6 in the present application, the client 6 mainly includes an acquisition unit 61 , a first recommendation unit 62 , a second recommendation unit 63 and a display unit 64 , which will be described separately below.

[0096] The obtaining unit 61 is used to obtain sample data of the user, where the sample data is omitted information, false information, coarse-grained information or fine-grained information of the user's personal information. In a specific embodiment, the acquisition unit 61 collects the personal information of the user on the client device, and selects and generates omitted information, false information or coarse-grained information according to a preset first mechanism; the first mechanism here includes: judging the personal information When the first sharing condition is not satisfied, the omission information is obtained according to the preset authority control mechanism; or, when the second sha...

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Abstract

The invention discloses a privacy protection mobile service recommendation method, a client and a recommendation system, and the privacy protection mobile service recommendation method comprises the following steps: obtaining sample data of a user, the sample data being saving information, false information, coarse-grained information or fine-grained information of personal information of the user; receiving a first service recommendation list from a network service provider according to the sample data; screening and generating a second service recommendation list from the first service recommendation list according to the fine-grained information of the user; and displaying the second service recommendation list to the user. The first service recommendation list is downloaded to the local client to assist in generating the second service recommendation list meeting the user requirements; therefore, on the premise of ensuring that the personal information of the user is not invaded bya network service provider, the function of providing accurate recommendation service for the user is realized, the balance between mobile service recommendation precision and user privacy protectioncan be maintained, and the user can better manage the personal information.

Description

technical field [0001] The invention relates to the technical field of network services, in particular to a privacy protection network service recommendation method and a recommendation system thereof. Background technique [0002] The personalized recommendation system is an advanced intelligent platform based on massive data mining. After collecting a large amount of user data, the platform analyzes the user's interests and hobbies through data mining technology, and then recommends products or services of interest to users. . With the popularity of mobile devices, personalized recommendation systems are also widely used in mobile services. However, in the process of data collection and data mining analysis, the risk of user privacy leakage is also increasing, which in turn affects users' recommendations for mobile services. system acceptance. [0003] The method of collecting personal data of target users and transmitting personal data to a server for calculation to obt...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06F21/62
CPCG06F21/6245G06F16/9535
Inventor 刘洋徐睿峰王轩张伟哲廖清蒋琳李泽睿胡甄博石路
Owner HARBIN INST OF TECH SHENZHEN GRADUATE SCHOOL
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