Web page classifying method and apparatus

Abstract

The invention provides a web page classifying method and apparatus. The method comprises the steps of: analyzing a plurality of web page elements from a to-be-predicted web page; predicting candidate web page classifications to which the to-be-predicted web page belongs according to the web page elements respectively; and comparing the candidate web page classifications predicted by the web page elements respectively, and determining final web page classification of the to-be-predicted web page. According to the method, a full-automatic classifying process is realized, the manual operation is not required, the web page classifying efficiency is greatly improved, especially massive web pages of the whole network and web pages newly generated in the internet can be quickly and effectively classified, and the web page classifying timeliness is ensured.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to a method for classifying webpages and a device for classifying webpages. Background technique [0002] Web page classification plays a vital role in many Internet products. For example, in news media, the classification of news webpages plays a very important role in organizing news content reasonably and effectively and improving users' reading experience. [0003] The current webpage classification technology is mainly a semi-automatic way to classify webpages, which is completed through algorithms and manual review. In the algorithm stage, a traditional classification algorithm (such as naive Bayesian) is used to initially classify webpages. , but the main problem at this stage is that the accuracy rate cannot be guaranteed; in the manual review stage, in order to improve the classification accuracy rate, manual review is generally required. [0004] Since the above sch...

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Problems solved by technology

[0003] The current webpage classification technology is mainly a semi-automatic way to classify webpages, which is completed through algorithms and manual review. In the algorithm stage, a traditional classification algorithm (such as naive Bayesian) is used to initially classify webpages. , but the main problem at this stage is that the accuracy rate cannot be guaranteed; in the manual review stage, in order to improve the classification accuracy rate, manual review is generally required

[0004] Since the above scheme is semi-automated, it cannot meet the requirements when faced with a large amount of data that needs to be classified; and, because the classification of web pages is generally defined manually in the early stage, the scalability is poor; the timeliness of the entire system is very poor , due to the need to go through two stages, and the time cost of manual review in the second stage is very high, the timeliness of the entire system cannot be guaranteed

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