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Network social relationship knowledge graph generation method and system based on artificial intelligence

A technology of network socialization and relational knowledge, applied in other fields such as database retrieval, instrumentation, electronic digital data processing, etc., can solve the problem of network social experience relationship without comprehensive consideration of social relationship, etc.

Inactive Publication Date: 2019-11-26
NANJING INST OF INTELLIGENT COMPUTING CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Based on this, it is necessary to address the defects or deficiencies in the prior art and provide an artificial intelligence-based method and system for generating network social relationship knowledge graphs, so as to solve the problem of not comprehensively considering multiple social network platforms when generating network social experience relationships in the prior art Disadvantages of integrating time and social network experience into social relationships in

Method used

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  • Network social relationship knowledge graph generation method and system based on artificial intelligence
  • Network social relationship knowledge graph generation method and system based on artificial intelligence
  • Network social relationship knowledge graph generation method and system based on artificial intelligence

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0071] Such as figure 1 As shown, a method for generating a network social relationship knowledge graph is provided, including the step S100 of acquiring experience, the step S200 of extracting experience, the step S300 of intersecting experience, the step S400 of acquiring intersection information, and the step S500 of generating relationship.

[0072] The experience obtaining step S100 is used to obtain the network social experience of each network user. The network social experience includes the personal network social experience of the network user, also includes the network social experience obtained from network information such as social networking sites, and also includes all information that includes the network user's experience.

[0073] The experience extraction step S200 is used to extract each experienced time period and the social network where the network user is in the time period from each network user's network social experience. The social network where th...

Embodiment 2

[0093] Such as figure 2 As shown, according to the network social relationship knowledge graph generation method provided in Embodiment 1,

[0094] Wherein, the experience acquisition step S100 includes the information reply and information release experience acquisition step S110.

[0095] The information reply and information release experience obtaining step S110 is used to obtain the information reply experience and information release experience in the network social experience of each network user.

[0096] Network social experience can be input by network users, or can be obtained from social networks or other websites or databases, from which information reply experience and information release experience can be extracted.

[0097] For example

[0098] Zhang San

[0099] Information reply experience

[0100] 2010.9-2014.7 A1 Social Network B11 Theme

[0101] 2014.9-2017.7 A2 Social Network B21 Theme

[0102] Information release experience

[0103] 2017.9-2018.7 A...

Embodiment 3

[0130] Such as image 3 As shown, according to the network social relationship knowledge graph generation method provided in Embodiment 1,

[0131] Wherein, the intersection information obtaining step S400 includes a first intersection information obtaining step S410.

[0132] The first intersection information acquisition step S410 is used to obtain the time period and social network information of the intersection part for every two experiences belonging to different network users whose time period intersection is not empty and the social network intersection is not empty by matching the experience .

[0133] The specific steps of finding the social network intersection of two network user experiences (one experience of network user A and one experience of network user B)

[0134] From the social network information experienced by network user A, the first-level social network name (for example, based on the identification and extraction of keywords such as "Sina Weibo" an...

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Abstract

The invention discloses a network social relationship knowledge graph generation method and system based on artificial intelligence. The method comprises an acquisition step, an extraction step, an intersection step, an intersection information acquisition step, a relationship generation step, a knowledge graph generation step and an entity acquisition step. According to the method and the system,through a network social relation knowledge graph generation technology based on artificial intelligence and big data, the intelligence and high efficiency of network social relation knowledge graphgeneration are improved.

Description

technical field [0001] The present invention relates to the field of information technology, in particular to a method and system for generating a network social relationship knowledge map based on artificial intelligence. Background technique [0002] In the process of realizing the present invention, the inventor found that there are at least the following problems in the prior art: the existing network social experience relationship is often limited to the same social network, for example, analysis is only based on Weibo, or only based on Renren. And so on, and the factor of time is not taken into account when analyzing the relationship of network social experiences. Therefore, the prior art still needs to be improved and developed. Contents of the invention [0003] Based on this, it is necessary to address the defects or deficiencies in the prior art and provide an artificial intelligence-based method and system for generating network social relationship knowledge gr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/901G06F16/9035G06Q50/00
CPCG06Q50/01G06F16/9024G06F16/9035
Inventor 朱定局刘彥辰黄君
Owner NANJING INST OF INTELLIGENT COMPUTING CO LTD
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