Repeat network access analysis method based on vector space model (VSM)

Abstract

The invention belongs to the technical field of information communication, and in particular relates to a repeat network access analysis method based on a vector space model (VSM). The analysis method comprises the following steps: determining a subscriber number set to be matched and an additional subscriber number set; extracting feature items of subscriber numbers to be matched; extracting feature items of additional subscriber numbers; obtaining tickets for the subscriber numbers to be matched and tickets for the additional subscriber numbers; forming a ticket set for the subscriber numbers to be matched and a ticket set for the additional subscriber numbers; respectively determining different feature items of the ticket set for the subscriber numbers to be matched and the ticket set for the additional subscriber numbers; calculating weight values of the feature items in each ticket for the subscriber numbers to be matched and each ticket for the additional subscriber numbers; and calculating the similarity between the two types of tickets for the subscriber numbers so as to determine whether the subscriber numbers are the numbers for repeat network access. The repeat network access analysis method provided by the invention has the advantages of faster computation speed and higher recognition accuracy.

Description

technical field [0001] The invention belongs to the technical field of information communication, and in particular relates to a re-entry network analysis method based on a vector space model. Background technique [0002] At present, an important problem faced by telecom operators is the phenomenon of re-entry, that is, when a mobile user already has a mobile number, he buys a new number from the same mobile operator to join the network, and the new number completely or partially replaces the original old number. Number. [0003] 1. There are many reasons for a large number of re-entry users, mainly as follows: [0004] (1) There are a large number of tariff-sensitive customers. Customers are more sensitive to tariffs. When a new tariff package appears or a certain package has a discount, these tariff-sensitive customers will jump in the network. Usually, these customers are low-value customers with low ARPU (ARPU-Average Revenue Per User, average revenue per user), and ...

AI Technical Summary

Problems solved by technology

[0006] (3) There are a large number of customers who are not allowed to locate

Disadvantage: At present, many users do not have user information in the customer management system of mobile communication providers

Disadvantage: There is no IMEI on many mobile phones, so this method cannot be used to identify effectively

Disadvantages: The call fingerprint algorithm based on contact circle information is not very effective in controlling re-entry users due to low recognition accuracy and long recognition time

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