Method for acquiring network service status based on microblog big data

A network service and data acquisition technology, applied in the field of big data and SVM classifier, can solve the problems of large scale of big data and high complexity of network service status, and achieve the effect of reducing scale

Inactive Publication Date: 2016-01-06
WUHAN POST & TELECOMM RES INST CO LTD
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Problems solved by technology

[0006] The technical problem to be solved by the present invention is that the existing network big

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  • Method for acquiring network service status based on microblog big data
  • Method for acquiring network service status based on microblog big data

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Embodiment Construction

[0044] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0045] The embodiment of the present invention provides a method for obtaining network service status based on microblog big data, such as figure 1 with figure 2 As shown, the method includes the following steps:

[0046] Step S1. Randomly obtain a small part of microblog data in the microblog data set as a training data set.

[0047] In this embodiment, the collected microblog data set has millions of microblogs, and several thousand of them can be randomly obtained as the training data set.

[0048] Step S2, preprocessing the training data set, that is, deleting meaningless microblogs.

[0049]Among them, meaningless microblogs include spam microblog texts and advertising marketing microblog texts. The algorithm for deleting meaningless microblogs used in this embodiment is designed with reference to the Bayesian spam filtering algorith...

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Abstract

The present invention discloses a method for acquiring a network service status based on microblog big data. The method comprises: using a part of microblogs of a microblog dataset as a training dataset, using the remaining microblogs as a testing dataset, and preprocessing the training dataset and the testing dataset; performing marking, initialization operation, word partitioning and word pausing on training data, performing feature selection on the training dataset to obtain a feature term dictionary, generating feature vectors according to the feature term dictionary to obtain a feature vector set, and performing training on the feature vectors to obtain an SVM classifier; and acquiring a preset keyword library; presorting testing data, performing initialization operation, word partitioning and word pausing on testing data of which the presorting fails; according to the feature term dictionary, generating feature vectors of the testing data of which the presorting fails, to obtain a feature vector set; performing classification by using the SVM classifier to obtain a classification result, and integrating the classification result and a presorting result. The method effectively reduces scale and complexity of network big data.

Description

technical field [0001] The invention relates to the fields of big data and SVM (Support Vector Machine, Support Vector Machine) classifiers, in particular to a method for acquiring network service status based on microblog big data. Background technique [0002] With the continuous development and popularization of telecommunication networks, the complexity of the network continues to increase, resulting in an astonishing amount of data. Based on DDN (DataDrivenNetwork, Data Driven Network), big data technology is used to analyze network big data and discover the clues and clues implied in it. Laws to help people perceive and predict the status of network services. [0003] According to data types, network big data can be divided into three categories: self-media data, log data and rich media data. Weibo, as a kind of self-media data, has concise content, clear information and timeliness, and has become the most popular in recent years. The new social media and information ...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06F17/30
CPCG06F16/35G06F18/2411
Inventor 许德玮郝俊瑞向智宇郭嘉
Owner WUHAN POST & TELECOMM RES INST CO LTD
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