Swarm intelligence perception system user recommendation method

A crowd-sensing system, a technology for recommending users, applied in data processing applications, instruments, resources, etc., can solve the problems of low information utilization, high task push overhead, etc., and achieve the effect of large benefits and effective user recommendation

CN108038622AActive Publication Date: 2018-05-15BEIJING INSTITUTE OF TECHNOLOGYGY
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2018-05-15

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Abstract

The invention relates to a swarm intelligence perception system user recommendation method and belongs to the technical field of swarm intelligence perception system optimization. The method comprisesthe steps that (1) user historical data is acquired; (2) users and task feature vectors are quantified, and a user-task data quality matrix is established; (3) a task message pushing group is obtained from an original user group; (4) final participation users are selected from the pushing group; and (5) final participation user data is acquired, and a user-figure data quality matrix is updated. Compared with the prior art, personal interests and preferences of the users and the problem that different tasks completed by the users are different in data quality are fully considered in the method, and therefore user recommendation can be performed more effectively; and for the users interested in participating in the tasks, the final users participating in the tasks are selected according tohistorical participation data quality of the users and the scale of the currently selected users, therefore, a platform can guarantee completion of the tasks and obtain maximum benefit.
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Description

technical field

[0001] The invention belongs to the technical field of crowd-sensing system optimization, and in particular relates to a method for recommending users of the crowd-sensing system, which is used to reduce task pushing costs and improve the platform revenue of the crowd-sensing system. Background technique

[0002] At present, the crowd-sensing system has a large number of registered users, which causes the problem of excessive network overhead for platform push tasks. At the same time, due to the different interests and preferences of users in the swarm intelligence network system and the uneven quality of users, the utilization rate of task push information is too low. A feasible way to solve the above problems is to evaluate the data quality of registered users and use relevant recommendation methods to obtain high-quality user groups. User data quality is usually fixed during the execution of a task, which can measure the performance of the user in the tas...

Examples

Embodiment Construction

[0046] The method of the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0047] Such as figure 1 Shown is the feedback status of different users when the crowd sensing system (platform) releases a task. When the platform Platform releases a task, there are three different types of user groups in the user Mobile Users, namely the normal user Preferred User, the uninterested user User Non-interested User and malicious user MaliciousUser, aiming at the Information Push pushed by the platform, the behaviors of these three types of users are respectively submitting feedback quotation Reply Budget, not participating and feedback quotation Reply Budget.

[0048] Below to figure 1 The model shown takes the ambient temperature detection task in a certain area as an example to illustrate the implementation process of the present invention.

[0049] In the group intelligence sensing task of environmenta...