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A Method of Entity Relationship Extraction Based on Multi-Object Fusion

An entity relationship, multi-objective technology, applied in the field of natural language processing, can solve the problems of low accuracy, low accuracy, and lack of personal descriptions in user portrait discovery and matching, and achieve the effect of precise entity relationship extraction and improved accuracy.

Active Publication Date: 2022-04-19
北京半人科技有限公司
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AI Technical Summary

Problems solved by technology

[0008] The purpose of the present invention is to aim at the discrete distribution of Internet public opinion and other related Internet speech records in the Internet. When using the existing Internet public opinion control mechanism to identify, there will be defects such as missing personal descriptions and low accuracy. A new method of entity relationship extraction based on multi-objective fusion is proposed to deal with technical problems such as different user cognition caused by different message gaps in APP, and low accuracy of user portrait discovery and matching.

Method used

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  • A Method of Entity Relationship Extraction Based on Multi-Object Fusion
  • A Method of Entity Relationship Extraction Based on Multi-Object Fusion
  • A Method of Entity Relationship Extraction Based on Multi-Object Fusion

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Embodiment

[0055] An entity relationship extraction method based on multi-objective fusion, such as figure 1 shown, including the following steps:

[0056] Include the following steps:

[0057] Step 1.1: Determine the validity of the collected data.

[0058] Step 1.2: Determine the Keyword training corpus of the user portrait entity relation word set.

[0059] In the present embodiment, personal user messages in WeChat, Tencent QQ, and whatsapp are selected and released dynamically to form the training corpus Keyword, which contains a total of 140,000 texts.

[0060] Step 1.3: Build a specific user portrait entity relationship word set.

[0061] Include the following steps:

[0062] Step 1.3.1: Construction of word vectorization model.

[0063] Include the following steps:

[0064] Step 1.3.1.1: For the Keyword corpus obtained in Step 1.2, use LSTM+CRF to segment all the text in the Keyword to obtain a single-sided user portrait after word segmentation.

[0065] Step 1.3.1.2: Scre...

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Abstract

The invention relates to an entity relationship extraction method based on multi-target fusion, which belongs to the technical field of natural language processing and aims to effectively solve the problem of inconsistent user cognition and low accuracy of user portrait discovery and matching caused by different messages of social APPs on the Internet. and other technical issues. This method combines the deep learning feature extraction model and CRF decoding to extract chats and dynamic records in different social APPs. By constructing a record aggregation method, the discovery and identification of users between different social APPs is realized. This method can automatically analyze and identify different social APP user portraits in the Internet environment, and associate different social APP accounts with the same user according to the similarity of user portraits. Compared with the traditional user discovery method, this method improves the accuracy of user identification in different APPs, and realizes a more accurate entity relationship extraction method based on multi-objective fusion.

Description

technical field [0001] The invention relates to an entity relationship extraction method based on multi-object fusion, in particular to an entity relationship extraction method based on multi-object fusion based on a deep learning feature extraction model, and belongs to the technical field of natural language processing. Background technique [0002] In the 5G era, the emergence of social apps has changed people's lives. The social APP system has become the most popular mode of making friends. [0003] Social APPs provide users with the function of making friends with strangers, and users contain a lot of information in communication with strangers. Although social apps can meet user needs, most users use multiple social apps at the same time or have multiple accounts for the same social app. Taking China News as an example, the account name on Sina Weibo is CCTV China News, and the account name on WeChat Official Account is CCTV News. For authoritative organizations, bec...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/906G06F16/9535G06F40/295
CPCG06F16/9535G06F16/906G06F40/295
Inventor 苏岩毛煜朱一凡祝永贺
Owner 北京半人科技有限公司
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