A method and system for identifying harassing calls

Abstract

The invention discloses a method and system for identifying and analyzing harassing calls based on a social relationship chain and a reputation level propagation model. The method can use a multi-source database and / or an algorithm engine to establish an algorithm library for extracting harassing calls. Carry out multi-dimensional association analysis on the communication behavior characteristics, geographical characteristics, time characteristics and number characteristics of the phone number, establish a social relationship map of the caller number, and build a social relationship chain of the caller number. At the same time, through the establishment of a three-dimensional integrated reputation level communication model, combined with the analysis of the social relationship chain of non-preset harassing calls, the accuracy of research, judgment and identification of non-preset harassing calls is improved.

Description

technical field [0001] The invention relates to the communication field, and is particularly applicable to a method and a system for identifying incoming communication calls. Background technique [0002] In recent years, the problem of harmful information such as harassing phone calls has become increasingly prominent. Some unscrupulous companies or individuals have taken advantage of the convenience of the above-mentioned services to distribute commercial harassing information indiscriminately, which has brought great trouble to telecommunications users, violated the legitimate rights and interests of the majority of telecommunications users, and may even Endanger social stability and national information security. [0003] Harassing calls are a global problem brought about by the rapid development of information technology. Developed countries represented by Europe and the United States have also encountered the problem of harassing calls in the process of information and...

AI Technical Summary

Problems solved by technology

[0010] How to improve the accuracy of identification is the main problem under the existing DNC mechanism. In the existing technology, the method of simply marking through the database first requires a large database for the identification method, and at the same time, the number marking is somewhat difficult for the operator. Whether the number belongs to the blacklist is dynamic. After some marketing calls are taken back by the operator after the shutdown, when new users use them, when the blacklist has not been updated, there will be identification errors. Therefore, relying solely on the above method , the recognition accuracy is low, and the recognition effect is not significant

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