Method for monitoring abnormal state of internet information

Abstract

The invention provides a method for carrying out abnormal state monitoring on Internet information by monitoring the change of the frequency of hot words in Internet information. The method comprises the steps of: 1. obtaining the word frequency data on the current day of general words existing on Internet web pages; 2. determining a set of hot words on the current day of Internet information by combining a hot word dictionary focused on by users; 3. determining the weight of every key word on the current day; 4. determining the abnormal threshold value of key words on the current day; 5. monitoring the abnormal degree of the key words on the current day and determining hot Internet information on the current day. The method of the invention monitors the change of the frequency of hot words in Internet information, calculates the abnormal degree of key words, forecasts the abnormal degree of the word frequency change of hot words and gives an alarm, thus ensuring that Internet information users can make a response at the first time.

Description

A method for monitoring abnormal state of Internet information technical field The invention belongs to the technical field of Internet information mining, and specifically relates to a method for tracking and monitoring the abnormal degree of Internet information. Background technique As the Internet has increasingly become the main media for people to publish and communicate information, the information on the Internet can more and more reflect the focus of people's attention and social hotspot events. Therefore, it becomes a natural demand to monitor hot issues and events reflected in network information. Both ordinary users and industry experts hope to have an automated tool or method to help them track the latest hot topics or news in the field they care about in real time, so as to understand the latest progress in this field. It is not difficult to find that, under normal circumstances, a large number of keywords in Internet information often mean the occurrence o...

AI Technical Summary

Problems solved by technology

Its main disadvantage is that it does not consider the historical mean and historical standard deviation of each term, so it is impossible to accurately measure abnormal hotspots according to the historical performance of high-frequency words and low-frequency words, and can only make a horizontal comparison of each term

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