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Efficient mass public opinion data information cluster matching method

A technology of data information and matching methods, applied in the field of data processing, can solve problems affecting the real-time performance of corporate public opinion information and blockage of public opinion information, and achieve the effect of matching speed and timeliness guarantee and real-time improvement

Active Publication Date: 2017-09-15
YLZ INFORMATION TECH CO LTD +1
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  • Abstract
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AI Technical Summary

Problems solved by technology

Moreover, the matching speed must be strictly controlled within milliseconds, otherwise it will lead to congestion of public opinion information in the end, affecting the real-time performance of corporate public opinion information

Method used

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  • Efficient mass public opinion data information cluster matching method
  • Efficient mass public opinion data information cluster matching method

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Embodiment Construction

[0020] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0021] The embodiment of the present invention provides an efficient mass public opinion data information cluster matching method, such as figure 1 with figure 2 shown, including:

[0022] S100, deploying Flume to each public opinion collection server, and collecting public opinion data information crawled from the Internet through Flume;

[0...

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Abstract

The invention provides an efficient mass public opinion data information cluster matching method. The method comprises the following steps of: deploying Flume onto each public opinion acquisition server and acquiring public opinion data information crawled from the internet through the Flume; storing the public opinion data information acquired by the Flume into a Kafka message queue; consuming public opinion data in real time from the Kafka and matching the public opinion data information and enterprise information in real time by utilizing a deployed Spark cluster; and displaying the successfully matched associated data information onto each web system. According to the method, a cluster matching framework is built to solve the conditions that the timeliness is bad and the matching speed is low; and test results show that both the matching speed and the timeliness are greatly improved after the cluster matching manner is adopted.

Description

technical field [0001] The invention relates to data processing technology, in particular to an efficient mass public opinion data information cluster matching method. Background technique [0002] Public opinion information refers to the information, news, information, intelligence, instructions, data and signals. At present, a lot of Internet public opinion information can be obtained online, and these public opinion information are very important to enterprises; the positive and negative, reprint volume, reading volume, and transmission speed of public opinion information all reflect the image of enterprises in the public mind at all times. However, Internet public opinion information is not related to which companies have negative public opinions, so many companies cannot monitor all public opinion information of their enterprises in the current period in real time. [0003] At present, there are a large number of enterprises, and the Internet public opinion informatio...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30H04L29/08
CPCG06F16/335G06F16/951H04L67/10
Inventor 吴梁斌庄国强巫锡燥梁丽琴
Owner YLZ INFORMATION TECH CO LTD
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