Active prediction method, system and computer-readable storage medium for abnormal phone calls based on ranking learning and ensemble learning

A sorting learning and integrated learning technology, applied in computer parts, computing, telephone communication, etc., can solve problems such as systems lacking user anomaly detection

Active Publication Date: 2020-10-30
UNIV OF JINAN
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0011] (2) The above methods are all passive solutions with hindsight, lacking a system that can actively detect abnormalities for users

Method used

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  • Active prediction method, system and computer-readable storage medium for abnormal phone calls based on ranking learning and ensemble learning
  • Active prediction method, system and computer-readable storage medium for abnormal phone calls based on ranking learning and ensemble learning

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Embodiment Construction

[0037] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0038] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0039] The present disclosure first performs selection and combination of phone features,

[0040] If the avera...

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Abstract

The disclosure discloses an active prediction method and system for abnormal calls based on ranking learning and integrated learning, including: collecting phone samples, selecting features of the phone samples based on analysis and combination; dividing the collected samples into a training set and a test set ;For the training set samples, sorting learning is used to process the data, and the obtained results are used as a new test set, and then n sets of new training sets are formed to continue through the learning model to obtain n sets of results, and then these n sets of results are passed through ensemble learning , output the final test result. The disclosure has beneficial effects: the accuracy rate of predicting abnormal calls using ranking learning and integrated learning is higher than that of single using ranking learning, and the conventional method is more active in predicting abnormal calls than our method, and can solve large-scale data problems.

Description

technical field [0001] The disclosure relates to the fields of machine learning and data mining, in particular to a method and system for actively predicting abnormal calls based on ranking learning and integrated learning. Background technique [0002] The statements in this section merely enhance the background related to the present disclosure and may not necessarily constitute prior art. [0003] Passive detection method is currently the main form to solve the problem of abnormal phone identification, that is, after a phone is flagged by a large number of users, it will be identified as an abnormal phone. However, as fraudulent calls appear in more and more diverse forms and involve a wider range, passive detection methods are insufficient in information mining and feature analysis, resulting in bottlenecks in accuracy and timeliness. The development of big data technology has made personal information leaked on various platforms. In order to solve this problem, many so...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04M3/22G06K9/62
CPCH04M3/2272H04M3/2281G06F18/24G06F18/214
Inventor 纪科刘健孙润元陈贞翔马坤王琳袁雅涵
Owner UNIV OF JINAN
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