Method and system for identifying same user among different platforms
A user and platform technology, applied in character and pattern recognition, data processing applications, special data processing applications, etc., can solve the problems of uncommon accounts, difficult to judge whether two Weibo belong to the same user, etc., to achieve good development, high The effect of accuracy
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[0040] Example one:
[0041] This embodiment provides a method for identifying the same user between different platforms, figure 1 The flowchart of this embodiment is shown, including:
[0042] Step S101: Collect a preset number of text information published by users on the first platform and the second platform;
[0043] Specify two platforms, such as Sina Weibo and Tencent Weibo, to collect a preset number of text messages posted by users of the two Weibo platforms. The specific collection process is as follows:
[0044] Step S201: construct a user queue;
[0045] Step S202: Select a user as a seed user and add it to the user queue;
[0046] Step S203: Take out a user from the user queue, grab the user profile information and published text information through the API provided by Weibo. The user profile information includes the followed user and the followed user, and the following Users and followed users are added to the user queue;
[0047] Step S204: Repeat the process of capturing...
Example Embodiment
[0062] Embodiment two:
[0063] This embodiment provides a system for identifying the same user between different platforms, figure 2 Shows a schematic structural diagram of this embodiment, including:
[0064] The collection module 101 is configured to collect a preset number of text information published by users on the first platform and the second platform;
[0065] The marking module 102 is used to mark a part of the text information;
[0066] The first sample acquisition module 103 is configured to use the labeled text information in the text information as a labeled sample, and use the unlabeled text information in the text information as a sample to be tested;
[0067] The second sample acquisition module 104 is configured to use the LDA model to extract topic features from the labeled samples and the samples to be tested, respectively perform cosine similarity calculations on the extracted topic features, and use the obtained similarity values as training samples respectivel...
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