Intelligent web page classifier based on user behaviors

Abstract

An intelligent web page classification device based on the user's behaviors: (1) Perform background input with an initial classification sample group for training, so as to gain a clustering center of each classification in the characteristic space. (2) Receive a URL input by the user input before catching and analyzing corresponding pages on the background; then, output texts with index value in the page. Moreover, extract a characteristic set according to the user-input content and web page contents; then, perform feedback modification for the characteristic space in the initial classification sample group and adjust the characteristic weight factor in the vector space. (3) Use the user-selected classification device to perform automatic classification for the texts in the previous step of the created texts and output results. When the user executes a search, the classification device can automatically determine the classification of each result and perform gradual adjustment for the classification device; the more times the user executes the search, the more accurate the classification of the web page classification device will be, so as to help different users effectively reduce the size of the set of the search result before locating necessary information more accurately.

Description

technical field [0001] The invention relates to a technology for intelligently classifying webpages, in particular, the intelligent learning of classifiers is carried out in combination with user behavior characteristics and webpage content. Background technique [0002] Existing webpage classifiers mainly include two categories: manual classification. For example, YAHOO's directory search is to manually classify the files stored in the local database. Although the classification accuracy is high, the efficiency is very low, the update speed is slow, and the maintenance workload is heavy. Automatic classification. Using a computer system to replace manual classification of web pages mainly includes two implementation methods: a classifier based on knowledge engineering and a classifier based on statistics. The former mainly relies on linguistic knowledge and needs to compile a large number of inference rules as classification knowledge. The search results are very accurat...

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