A webpage classification method, terminal equipment and storage medium

Abstract

The present invention relates to a method for classifying webpages, terminal equipment and storage media. The method includes: S1: collecting various types of webpages, constructing a graph structure according to at least two types of features in each webpage, and performing a classification of the types of webpages After marking, form a training set with all graph structures with type tags; S2: Construct a graph convolutional neural network model, train the graph convolutional neural network model through the training set, and use the trained model as a web page classification model; S3: For the webpage to be classified, after the graph structure is constructed according to the at least two types of features described in step S1, the webpage type corresponding to the graph structure is determined through the webpage classification model. The invention fully learns additional heterogeneous information such as text and pictures in webpages to construct a webpage classification model. Compared with existing webpage classification methods, it can effectively solve the limitations of webpage classification methods based on a single data structure, and can obviously solve webpage characteristics. Sparse problem.

Description

technical field [0001] The invention relates to the field of webpage classification, in particular to a webpage classification method, terminal equipment and a storage medium. Background technique [0002] With the rapid popularization of Internet technology, Internet applications are also booming. High-quality, personalized content is constantly emerging, and more and more netizens can share rich network resources. But at the same time, some illegal and criminal activities are also hidden in it, and a large amount of false information, advertising information, Internet fraud and other illegal and illegal information are released on the Internet, which seriously endangers the property safety of the majority of netizens. How to discover and identify this kind of bad text information and purify the network space requires an efficient and intelligent web page analysis method. [0003] The content information structure of the web page is diverse, with pictures, texts, videos a...

AI Technical Summary

Problems solved by technology

This method is less flexible and has the problem of low generalization ability; 2) building a classification model based on webpage content, most of the webpage features currently used are too single, such as only using text information or only using image information as the feature representation of webpages, It cannot fully represent the content information of the webpage, ignoring the information carried by other structural data, often ignoring the key information and causing the features to be more sparse, which has obvious limitations

Existing webpage classification methods have the following deficiencies: (1) by comparing webpage content or URLs at present, it is usually necessary to build a large-scale comparison library. High error rate and poor generalization; (2) At present, the classification model is built based on webpage content. Since only single-structure data is considered in the modeling process, but the information structure of webpage content is diverse, some webpages may only have text or pictures, etc.

Therefore, it is easy to see that the classification method based on single-structure data cannot be widely applied to all web page data, and cannot solve the problem of feature sparsity. The scope of application is very limited, and the model effect cannot be guaranteed.

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