Text retrieval method based on matrix weighted association rules and mixed expansion of front and back components

Abstract

The invention discloses a text retrieval method based on mixed expansion of front and back parts of matrix weighted association rules, First, the user queries and retrieves the document set to construct the related document set of the first-checked user. Then, the weighted value and frequency of the item set are fused with the total weighted value of the feature words and the total number of documents of the first-checked user. The frequent item set containing the original query term is mined. The candidate item set is pruned by item weight sorting, and by use of a confidence-correlation evaluation frame is used to excavate association rules from frequent item sets. Finally, the consequent association rules of the original query term and the consequent association rules of the original query term are used as extension words, and the extension words are combined with the original query term to retrieve the document set again to obtain the final retrieval result document and return it tothe user. The invention adopts the pruning method based on item weight sorting, improves the mining efficiency, adopts the weighted association rule before and after parts mixed expansion technology,and improves the text information retrieval performance.

Description

technical field [0001] The invention belongs to the field of information retrieval, and in particular relates to a text retrieval method based on matrix weighted association rules with mixed extensions of context and context. Background technique [0002] How to efficiently and accurately find more needed information from the ocean of information has always been a hot issue in the field of information retrieval. The current web search engines have alleviated people’s difficulties in retrieving information on the Internet to a certain extent. However, the current search engines or web information retrieval systems are often based on keyword mechanical symbol matching retrieval, which is difficult to avoid information overload and word retrieval. issues such as mismatches, for example, the query term is "computer", although "computer" describes almost the same meaning, but, to the information retrieval system, "computer" and "computer" are considered different search terms, I...

AI Technical Summary

Problems solved by technology

[0003] In order to solve the above-mentioned problems, the present invention proposes a text retrieval method based on matrix weighted association rules, which is suitable for the field of information retrieval, improves and improves the performance of information retrieval, and solves the problems of query topic drift and word mismatch in information retrieval

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