A network community user identification method and device

A network community and user identification technology, applied in the field of network community user identification methods and devices, can solve the problems that the identification performance and accuracy need to be improved, the characteristics are difficult to quantify, and the cost is high, so as to improve the identification performance and accuracy, improve the The effect of training speed and reducing time cost

Active Publication Date: 2019-05-21
BEIJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

However, the above methods are all statistics and mining of single-dimensional feature data, and the recognition performance and accuracy rate need to be improved; and in the process o

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  • A network community user identification method and device
  • A network community user identification method and device

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Embodiment 2

[0088] According to the embodiment of the present application, a network community user identification device is also proposed, such as figure 2 shown, including:

[0089] Extracting and generating module 201, for extracting the first N-gram feature of the network community text data collected in advance and generating the first word vector;

[0090] A training module 202, configured to train the first word vector based on a deep neural network and a cross-entropy cost function to obtain a text content analysis model;

[0091] The first analysis module 203 is configured to use the text content analysis model to analyze the text data of the user to be identified to obtain content attributes;

[0092] The second analysis module 204 is configured to use a preset behavior analysis model to analyze the behavior data of the user to be identified to obtain behavior attributes;

[0093] The identification module 205 is configured to identify the user to be identified according to t...

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Abstract

The invention discloses a network community user identification method and device, and relates to the technical field of machine learning and user identification. The method comprises the following steps: extracting a first N-gram feature of the pre-collected network community text data and generating a first word vector; Taking the cross entropy as a cost function, and training the first word vector by adopting a deep neural network to obtain a text content analysis model; Analyzing the text data of the to-be-identified user by using a text content analysis model to obtain a content attribute; Analyzing the behavior data of the to-be-identified user by using a preset behavior analysis model to obtain behavior attributes; And identifying the to-be-identified user according to the content attribute and the behavior attribute. In the invention, N-gram features are introduced, the target user identification is carried out based on the the user content and user behavior two-dimensional data, and identification performance and accuracy are greatly improved compared with existing single-dimensional data user identification.

Description

technical field [0001] The present application relates to the technical field of machine learning and user identification, and in particular to a method and device for user identification in a network community. Background technique [0002] With the continuous development of social networks, people are more willing to express their opinions and publish comments on hot events through public social platforms such as online communities and Weibo. The influence and dissemination ability of this kind of public platform are increasing day by day, which makes the influence of individuals also increase. Therefore, in many cases, it is more and more popular to accurately identify users based on users' publishing data and publishing behaviors in social networks. s concern. [0003] Currently, target user identification methods mainly use traditional statistical models or data mining algorithms based on machine learning, among which data mining algorithms based on machine learning ar...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06Q50/00G06N3/04G06N3/08
Inventor 吴旭许晋颉夏青戴雨伦
Owner BEIJING UNIV OF POSTS & TELECOMM
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