A method and device for classifying users according to server search log data

Abstract

The invention discloses a method and a device for classifying users according to search log data of a server. The method comprises the following steps: acquiring a query terms used by each of N users during searching from the search log data of the server and b access webpages which are searched according to each query term and are accessed by the users; performing segmentation processing on each query term and the b access webpages which correspond to each query term respectively to obtain c keywords which correspond to each query term; calculating the weights of the c keywords according to the occurrence times of the c keywords in each query term and the b access webpages; establishing a user behavior vector for each user according to the c keywords which correspond to each query term and the weights of the c keywords; calculating the similarity among the user behavior vectors of the N users; classifying the N users according to the calculated similarity.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a method and device for classifying users according to search log data of a server. Background technique [0002] With the development and popularization of computer technology, the demand for obtaining various information by searching servers is also increasing. At present, relevant webpages are mainly triggered by inputting query words, and the server provides the search results including the relevant webpages to the user, so as to allow the user to obtain relevant information. However, when the server provides the user with search results including relevant web pages, it cannot predetermine the user's interests or usage habits, and cannot predict how much information the user wants in the search results and how relevant it is, so that it cannot be targeted provide search results to users. And the user may need to visit multiple webpages displayed in the search results one ...

AI Technical Summary

Problems solved by technology

However, when the server provides the user with search results including relevant web pages, it cannot predetermine the user's interests or usage habits, and cannot predict how much information the user wants in the search results and how relevant it is, so that it cannot be targeted provide users with search results

However, users may need to visit multiple web pages displayed in the search results one by one, and then filter them to obtain the information they need, which is not efficient, so the actual results do not meet the needs of users.

In addition, the current mainstream search engine servers all have a click feedback mechanism, which ultimately makes these web pages that do not meet user needs always rank high, which actually deviates from user needs, resulting in low information search efficiency

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