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A point of interest recommending method and device

A point of interest, algorithm technology, applied in the field of privacy protection algorithm, can solve the problem of excessive exposure of user private information, and achieve the effect of solving privacy leakage and friendly way

Active Publication Date: 2019-01-29
XIAMEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, the purpose of the present invention is to overcome the deficiencies of the prior art, provide a method and device for recommending points of interest, solve the problem of excessive exposure of user privacy information in the process of recommending points of interest, and provide reasonable recommendations for users. On the premise of the points of interest, the user's privacy disclosure problem is solved in a more friendly way

Method used

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  • A point of interest recommending method and device
  • A point of interest recommending method and device
  • A point of interest recommending method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0065] figure 1 It is a flow chart of a method for recommending a point of interest provided by an embodiment of the present invention. This embodiment is applicable to recommending a point of interest to a user in a geographic information system. The method can be recommended by the point of interest provided by the embodiment of the present invention. implemented by a device, which may be implemented in software and / or hardware. refer to figure 1 , the method may specifically include the following steps:

[0066] S110. Acquire a differential privacy noise factor.

[0067] Specifically, the differential privacy noise factor in the embodiment of the present invention needs to meet the differential factor condition, and firstly, it is necessary to obtain the differential privacy noise factor satisfying the differential privacy condition. Next, the differential privacy conditions are explained through the definition of differential privacy: there are n records in the database...

Embodiment 2

[0090] figure 2It is a flow chart of a method for recommending points of interest provided by an embodiment of the present invention. On the basis of the above embodiments, this embodiment optimizes "obtaining differentially private noise factors". refer to figure 2 , the method may specifically include the following steps:

[0091] S210. Delete at least one friend relationship link of the user, and generate a new neighbor set of the user.

[0092] First, introduce the differential privacy decision theorem, if F: D→R k is a k-dimensional query function whose sensitivity is ΔF, then F(D)+Lap k (ΔF / ∈) satisfies ∈ - Differential privacy. Among them Lap k (λ) is a k-dimensional vector sampled from the Laplace distribution, and its standard deviation is

[0093] Specifically, delete a friend set F of user i i The relationship link of at least one friend in , where the deleted friends can be random, that is, they are no longer friends, and generate a new neighbor set F′ ...

Embodiment 3

[0104] image 3 It is a flow chart of a method for recommending a point of interest provided by an embodiment of the present invention. On the basis of the above-mentioned embodiments, this embodiment "according to the number of historical visitors to the point of interest in the target area and the actual geographical location of the user, based on the setting The location privacy protection algorithm is determined, and the radius of the virtual circle is determined to be optimized. refer to image 3 , the method may specifically include the following steps:

[0105] S310. Acquire a differential privacy noise factor.

[0106] S320. According to the differential privacy noise factor, determine the fuzzy similarity recommendation probability of friends between users based on the set social relationship privacy protection algorithm.

[0107] S330. Determine the population density of the point of interest according to the historical number of visitors to the point of interest ...

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Abstract

The invention relates to a point of interest recommending method and device. The method comprises the following steps: obtaining a differential privacy noise factor; determining a friend fuzzy similarity recommendation probability between users based on a set social relationship privacy protection algorithm according to the differential privacy noise factor; determining a radius of a virtual circle based on a set geographic position privacy protection algorithm according to a historical visitor number of a point of interest of a target region and an actual geographic position of a target user,wherein an area corresponding to the virtual circle is a privacy area of the user; According to the virtual circle, the geographic location distance recommendation probability between the users is determined, and according to the friend fuzzy similarity recommendation probability and the geographic location distance recommendation probability, the interest points are recommended to the users. Theinvention solves the problem that users' privacy information is exposed too much in the process of recommending points of interest, and solves the problem of privacy disclosure of users in a more friendly manner on the premise of recommending reasonable points of interest for users.

Description

technical field [0001] The present invention relates to the technical field of privacy protection algorithms, in particular to a method and device for recommending points of interest. Background technique [0002] With the rapid development of social networking sites, wireless networks, and mobile network devices, some location-based social networking services, such as Facebook, Weibo, and Foursquare, have attracted millions of users, and many users have integrated social user networks into their lives. In existing recommendation systems, users are provided with interesting content through mobile phones and processing user preference information. For example, recommended content can be Point of Interest (POI) to improve user experience. [0003] In GIS, a point of interest can be a house, a store, a mailbox, or a bus stop, etc. Usually, in the process of recommending points of interest to users, in order to obtain better recommendation results, the recommendation process in...

Claims

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Application Information

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IPC IPC(8): G06F16/9537G06Q50/00
CPCG06Q50/01
Inventor 曾一锋陈碧连霍永峰曹浪财
Owner XIAMEN UNIV
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