Group division-based meta-search engine personalized result recommendation method

Abstract

The present invention discloses a group division-based meta-search engine personalized result recommendation method. The method includes a first step of determining whether a meta-search engine is used for the first time, if yes, executing a second step, if not, executing a fourth step; the second step of constructing a user model; a third step of dividing users into groups; the fourth step of determining whether information needs to be searched, if yes, executing a fifth step, if not, executing a tenth step; the fifth step of acquiring a search result list; a sixth step of determining whether a user belongs to the user group, if yes, executing a seventh step, and if not, executing an eighth step; the seventh step of recommending search results; the eighth step of recording clicked search results; a ninth step of updating the user model; and the tenth step of terminating. According to the method, the user model is constructed for the user in meta-search, and the users are clustered and divided into groups, so that personalized search results are recommended to the users.

Description

technical field [0001] The invention belongs to the technical field of information processing, and further relates to a method for recommending personalized results of meta search engines based on group division in the technical fields of Internet information retrieval and personalized services. The invention can be applied in the field of meta-search engine optimization to satisfy user group division and perform personalized search result recommendation. Background technique [0002] At present, in the face of the continuous expansion of Internet information resources and the continuous increase of user needs, in order to solve the problems of low information coverage of traditional search engines, low overlap rate of retrieval results of different search engines, and the difficulty of a single search engine to meet user information retrieval needs, improve the user's Experience, a meta-search engine that can integrate the search results of multiple search engines and provi...

AI Technical Summary

Problems solved by technology

The disadvantage of this method is that the user needs to manually set or perform multiple search behaviors before the search engine can record, analyze, and obtain user interests, and a large number of manual settings will reduce the user's search experience and lead to the loss of users; there is no Divide user groups based on user interests, which cannot better provide appropriate recommendation information for users with common interests

The shortcomings of this method are: to express interest through resource locators, but due to the uncertainty of the network, resource locators may be invalid, so it is not suitable for expressing user interests; and only considering a single dimension, it is impossible to comprehensively Describe user characteristics

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