Risk identification method based on big data topic analysis and server
A big data and topic technology, applied in the field of big data, can solve problems such as difficult to divide and conquer, difficult to realize risk identification, etc., to achieve accurate and fast topic fraud risk identification, and achieve the effect of topic fraud risk identification
Active Publication Date: 2022-05-27
北京亿欧网盟科技有限公司
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However, there are still some defects in the implementation of the second aspect of technology. For example, in the process of processing abnormal topic data, it is difficult to achieve targeted divide-and-conquer processing, which makes it difficult to achieve accurate and rapid risk identification.
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[0048] Hereinafter, the terms "first", "second" and "third" etc. are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implying the number of indicated technical features. Thus, a feature defined as "first", "second" or "third" etc. may expressly or implicitly include one or more of that feature.
[0049] figure 1 A schematic flowchart of a risk identification method based on big data topic analysis provided by an embodiment of the present invention is shown. A risk identification method based on big data topic analysis may be implemented by a risk identification server, and the risk identification server may include a memory and a a processor; the memory is coupled to the processor; the memory is for storing computer program code, the computer program code comprising computer instructions; wherein, when executed by the processor, the computer instructions cause the risk The identification server performs the tech...
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The invention provides a risk identification method based on big data topic analysis and a server. Potential characteristics of abnormal topic interaction data contained in an abnormal topic interaction data record can be fully considered; besides, in view of a second fraud tendency description of a user session event matched with unfused abnormal topic interaction data, at least part of interaction data in the unfused abnormal topic interaction data is fused to corresponding risk tags of x data fusion lists, according to the embodiment of the invention, the data fusion list obtained by fusing the first fraud tendency description can be adaptively expanded and optimized through the second fraud tendency description of the user session event, so that the abnormal topic interaction data in the abnormal topic interaction data record can be divided and treated in a targeted manner; therefore, an accurate and simple analysis basis is provided for topic fraud risk identification, and accurate and rapid topic fraud risk identification can be realized.
Description
technical field [0001] The invention relates to the technical field of big data, in particular to a risk identification method and server based on topic analysis of big data. Background technique [0002] The innovation of a new generation of information technology has brought tremendous changes to the production and life of modern society. Technologies such as big data, cloud computing, and artificial intelligence have been widely used in all walks of life. As one of the foundations of the new generation of information technology, big data has a wide range of applications. The current era is the era of traffic and topics, and the applications of big data in traffic analysis and topic analysis are emerging one after another. Taking topic analysis as an example, big data topic analysis can be divided into two aspects. The first aspect is user demand analysis + information push, and the second aspect is security protection analysis + risk identification. For the first aspect...
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IPC IPC(8): G06F16/33G06F40/30G06N3/04G06F16/35
CPCG06F40/30G06F16/3344G06F16/35G06N3/045
Inventor 刘佩明赵如平
Owner 北京亿欧网盟科技有限公司