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Mobile user node networking method integrating geographic position and time characteristics

A user node and geographical location technology, applied in the field of mobile user node networking, can solve the problems of only considering the user's geographical location information, only considering the user's friend relationship, and not fully considering all the available information of the social network, etc., to achieve accurate measurement effect

Inactive Publication Date: 2019-07-26
ZHENGZHOU SEANET TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The existing technology for networking user nodes based on similarity only considers the user's geographical location information, or only considers the user's friend relationship, and cannot fully consider all the available information of the user in the social network, resulting in the accuracy of the user networking technology. low problem

Method used

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  • Mobile user node networking method integrating geographic position and time characteristics
  • Mobile user node networking method integrating geographic position and time characteristics
  • Mobile user node networking method integrating geographic position and time characteristics

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Embodiment Construction

[0044] Such as figure 1 As shown, the present invention provides a mobile user node networking method that integrates geographic location and time features, and the method includes:

[0045] Step 1) Use the existing neural network including convolutional neural network (CNN) and recurrent neural network (RNN) to extract the geographical location feature and time feature of the user node, and then divide the check-in time of the user node into several sub-times section; wherein, the geographical location feature is the geographical location where the user node has checked in or the geographical location of interest; the time feature is the time when the user node has checked in; and then the time when the user node has checked in is divided into several sub-time segments;

[0046] Step 2) setting corresponding time weights respectively for several sub-time periods obtained in step 1);

[0047] Step 3) Using a density-based clustering algorithm, the geographical locations that ...

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Abstract

The invention relates to a mobile user node networking method integrating geographic position and time characteristics, which comprises the following steps: 1) extracting the geographic position characteristics and time characteristics of a user node, and dividing the sign-in time of the user node into a plurality of sub-time periods; 2) setting corresponding time weights for the plurality of sub-time periods respectively; 3) aggregating the geographic positions signed in or interested by the user nodes in each sub-time period into N clusters according to an activity radius; 4) calculating thebehavior similarity between any two user nodes; 5) calculating the behavior similarity of the user nodes in all time periods of one day; 6) abstracting the user node social relation network into a graph structure and dividing the user node social relation network into a plurality of sub-communities, 7) calculating the friend similarity of any two user nodes in each sub-community, and 8) fusing the results of the step 4) and the step 7) to obtain the fused similarity.

Description

technical field [0001] The invention belongs to the technical field of social computing and social networks, and in particular relates to a mobile user node networking method that integrates geographic location and time features. Background technique [0002] With the increasing application of Internet and big data research, the analysis of user similarity in location social network has become one of the key issues in data mining and social network analysis. The user's access location trajectory in the real world reflects the user's interests and habits to a certain extent. Therefore, users with similar access location trajectories are likely to have the same interests and habits. Therefore, calculating the similarity of user behavior is the basis for realizing functions such as user community discovery, personalized travel recommendation, and itinerary planning based on location-based services. [0003] The user's action trajectory is only the manifestation or carrier of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06K9/62G06Q50/00
CPCG06N3/08G06Q50/01G06N3/044G06N3/045G06F18/2321
Inventor 盛益强陈婉杰廖怡
Owner ZHENGZHOU SEANET TECH CO LTD
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