Webpage training method and system and webpage prediction method and system

Abstract

The invention relates to a webpage training method and system and a webpage prediction method and system. The webpage training method comprises obtaining a prior probability table of classified keywords according to existing data which are associated with the classified keywords; preprocessing a webpage to be trained to obtain a webpage text to be trained; extracting features in the webpage text to be trained according to the prior probability table to obtain an association relation feature vector representation F1 between the webpage to be trained and a specified category; performing model training on the association relation feature vector representation F1 to obtain a classification result of the webpage to be trained. According to the webpage training method and system and the webpage prediction method and system, category systems which are strong in heterogeneity can be simultaneously processed, the large category systems can be processed through less training data, and the problem of data sparseness is largely solved due to the fact that the browsing and search behavior of a user on the whole Internet not just a website is collected.

Description

technical field [0001] The present application relates to the field of the Internet, and in particular to a classification and prediction of Internet access behaviors of users. Background technique [0002] With the continuous popularization of computer technology, modern society has already relied heavily on the convenience brought by information technology. As computer and network technology become more and more efficient, safe and reliable, more and more wholesalers, retailers and consumers choose to conduct commodity transactions on the Internet. Specific websites are becoming the most commercially valuable service providers on the Internet. [0003] Users can browse, search, compare prices, purchase, pay, and evaluate a series of actions on a specific website to purchase commodities that meet their business intentions. [0004] At the same time, the scale and number of specific websites are also growing. For example, Taobao, Tmall, JD.com, Amazon, Dangdang, and numer...

AI Technical Summary

Problems solved by technology

[0011] The main purpose of this application is to provide a webpage training scheme and a webpage prediction scheme to solve the problems of website heterogeneity, huge category system and data sparsity that are difficult to overcome in the prior art

Images