Microblog-based network user enhancement representation method

A technology for network users and Weibo, applied in the field of Weibo data, can solve problems such as expanding the network, enhancing network representation learning, etc., to achieve the effect of improving the accuracy rate

Active Publication Date: 2017-09-01
NAT UNIV OF DEFENSE TECH
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  • Application Information

AI Technical Summary

Problems solved by technology

Current research has not expanded the topology of the network from the textual information of the nodes to enhance the effect of network representation learning

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  • Microblog-based network user enhancement representation method
  • Microblog-based network user enhancement representation method
  • Microblog-based network user enhancement representation method

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Embodiment Construction

[0027] Aiming at the sparsity characteristics of the network structure, the present invention establishes a network user enhanced representation learning method combined with user-generated text information based on the above assumptions, and realizes the inference task of user gender and age based on user feature representation.

[0028] The present invention will be described below in conjunction with the accompanying drawings and specific embodiments. First, give the following formal definition:

[0029] In a social network, a node corresponds to a user, and each node corresponds to a large amount of text information, representing the historical blog post information of the corresponding user. Assuming that G represents the network, then G=(V, E, T), where, V={v i} is the set of user nodes, E={(v i , v j )} is a binary edge set, each edge corresponds to a weight w, where w∈{0,1}, T={t i} is a collection of user-generated blog posts. Therefore, the research goal of the ...

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Abstract

The present invention discloses a microblog-based network user enhancement representation method. The method belongs to the field of microblog data mining, and particularly to a network representation learning method targeted at microblog data. The method comprises: in consideration of colloquial features of microblogging short texts, performing preprocessing on the texts in a targeted way, so as to reduce effects of noise data; by using an LDA theme model, generating feature representation of a historical blog text of user, and calculating cosine similarity between blog text features of any two users, so as to construct a potential friend relation network; and integrating structure information of an original network, and fusing a potential friend relation into the original network, to obtain a modified network structure. According to the method disclosed by the present invention, by using the potential friend relation network extracted from the user-generated text, the original network topological structure is modified, so as to obtain more accurate feature representation of microblog user nodes. Compared with the network representation learning method that only considers network structures, the method obviously improves accuracy of gender and age inference.

Description

technical field [0001] The invention belongs to the microblog data mining field, and in particular relates to a network representation learning method for the microblog data. Background technique [0002] The Internet in the Web2.0 era is gradually evolving into a ubiquitous information dissemination platform. New social media such as Twitter and Weibo that are oriented to Social Networking Services (SNS) are rapidly gaining the favor of the public. The latest statistics show that Twitter has 310 million monthly active users and Sina Weibo has 297 million monthly active users. People use social media to express opinions, share information, communicate and interact, and social media rely on social networks to disseminate and spread news, which has a profound impact on politics, economy, culture, education and other fields. Therefore, the characteristics of online social network data, such as large scale, various forms, complex structure, and dynamic changes, as well as the f...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/62G06Q50/00
CPCG06F16/9535G06Q50/01G06F18/2411
Inventor 胡玥贾焰周斌杨树强韩伟红李爱平黄九鸣江荣全拥邓璐刘强张涛童咏之刘心韩文祥
Owner NAT UNIV OF DEFENSE TECH
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