User behavior-based search method and system

Abstract

The invention provides a user behavior-based search method and system. The method includes that a basic search server generates search result pages in accordance with search terms input in a search engine by a user; an ordering server obtains corresponding tags in a pre-generated mapping relationship according to the search terms, tags the search result pages with the tags in the highest similarity with the search result pages, and classifies the search result pages with the same tags into a class; the ordering server obtains an interest class of the corresponding tags of the search result pages in accordance with the correspondence between preset interest classes and web pages, matches pre-generated user interest classes with the classes of the tags, increases the weight value of the search result pages corresponding to matched tags, and pushes the search result pages ordered according to the weight value to the user. According to the technical scheme, the user behavior-based search method and system can provide targeted and personalized search results to the user, thereby improving the search efficiency.

Description

【Technical field】 [0001] The invention relates to the search technology in the Internet field, in particular to a search method and system based on user behavior. 【Background technique】 [0002] Currently, search engines adjust the order of search results based on users' click behavior and related search terms in the search engine. For example, among the top ten search results, if users click on the fifth search result far more than The first four search results indicate that the fifth search result matches the search term better than the first four search results; or, the user continuously enters two search terms "apple" and "iPhone" to indicate the user's real needs It is to search for "iPhone", but the search result of the first search term does not give users satisfactory search results. Therefore, the search engine obtains user behavior feedback in this way and adjusts the search results. [0003] However, when the search engine adjusts the search results, the amount o...

AI Technical Summary

Problems solved by technology

[0003] However, when the search engine adjusts the search results, the amount of user information obtained is less, and the effectiveness is low. For example, the search engine can only obtain the information of whether the user opens a certain search result, but does not know whether the user has opened the search result. Satisfaction with the results; moreover, search engines analyze large-scale user data, and then adjust the search results, so they adjust the search results for general search requirements, and cannot effectively distinguish different semantic information of unified search terms, and cannot be based on user preferences. Interests and hobbies are tended to be adjusted, so it is not possible to provide users with more targeted and personalized search results. The level of personalized service of search engines is low. The burden of the engine, the search efficiency is low; for example, for the search term "apple" with different semantics, the search term contains two semantic information: fruit and mobile phone, the adjustment of the number of large-scale users will lead to a large demand for semantic information Overwrite another semantic information

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