Query expansion method based on user query association degree

Abstract

The invention relates to a query expansion method based on a user query association degree. The method comprises the following steps of: step 1) making statistics on the total number of web pages browsed by a user; step 2) dividing interest types; step 3) making statistics on the number of the interest types contained in the web pages browsed by the user and the number of the web pages; step 4) calculating interest preference weights of the user to the interest types; step 5) constructing a user preference model of the user; step 6) constructing a plurality of user preference models with methods in the steps 1) to 5); step 7) forming multiple user groups; and step 8) forming a search space by document click information of all users in the user group. According to the method, users closely related to user interests are taken as background knowledge and bases of query expansion, and based on this, an associative relationship among query words is analyzed by utilizing associative query, so that the problem of low primary retrieval quality is solved and the retrieval efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of network information search, and in particular relates to a query expansion method for query correlation between users. Background technique [0002] With the development of Internet technology and the rapid growth of network information, the Internet has become the world's largest knowledge base and an important source of information for people. The search engine that uses keywords to search for relevant network information has helped people to quickly find the information they need from the vast information resources to a certain extent, but it still faces some problems that need to be solved urgently. Through the research and analysis of search engine logs, it is found that 49% of user queries have only one word, and 33% of queries consist of two words. Users use an average of 1.4 words to describe their query content, and information with short query strings often cannot Provides enough information to...

AI Technical Summary

Problems solved by technology

Most of the expansions are only based on the surface of the keywords, but in fact, there are many ambiguities in the keywords themselves, for example: "apple" may be a computer brand or a fruit, and "rocket" may be a search for aerospace information. , you can also retrieve the information of the NBA Rockets. According to the statistical analysis of logs, only 20% of users express the same concept with the same search term, which reduces the efficiency of retrieval

[0004] 2) The retrieval of user's personal information is not fully utilized, resulting in the existence of query drift problem

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