Text retrieval method based on Copulas function and pseudo-correlation feedback rule extension

Abstract

The invention provides a text retrieval method based on Copulas function and pseudo-correlation feedback rule extension. The method comprises the steps: inquiring and retrieving a Chinese text original document set by a user; extracting front n initial detection documents from an initial detection result to construct a pseudo-correlation feedback document set; and mining rule extension words in the pseudo-correlation feedback document set by utilizing a Copulas-function-based support degree-confidence framework, combining the extension words with the original query to form a new query, realizing pseudo-correlation feedback rule extension, retrieving a Chinese document again by the new query, obtaining a final result document, and returning the final result document to the user. According to the method, a Copulas function is utilized to comprehensively unify classical generalized distribution taking item set frequency as measurement and probability distribution taking item set weight asmeasurement of a text document feature word item set into an item set support degree and a confidence degree; high-quality extension words can be mined to achieve pseudo-correlation feedback rule extension, the Chinese text information retrieval performance is improved, and the method has good application value and popularization prospects.

Description

technical field [0001] The invention relates to a text retrieval method based on Copulas function and pseudo correlation feedback rule expansion, belonging to the technical field of information retrieval. Background technique [0002] Current search engines and web information retrieval systems do not completely solve the problem of query topic drift and word mismatch, which leads to the degradation of web retrieval performance. With the development of network technology, the rapid growth of digital resources, and the advent of the era of big data, the above-mentioned problems are more prominent. How to enable users to quickly find the information resources they need, reduce query topic drift and word mismatch problems to meet user information needs, It is an important problem in the field of information retrieval that needs to be solved urgently. Query expansion is one of the core key technologies to solve the above problems. Query expansion refers to modifying the weight ...

AI Technical Summary

Problems solved by technology

In the past ten years, scholars have carried out research on query expansion-based information retrieval methods from different perspectives, and some effective information retrieval methods have been produced. For example, a personalized information retrieval method based on query expansion proposed by Zhou Dong et al. ( See patent literature: Zhou Dong; Wu Xuan; Zhao Wenyu, a personalized information retrieval method based on query expansion, authorized publication number: CN106547864B, application (patent) number: CN201610932970.4), a query expansion based and classified information retrieval method (see literature: Yue Wen, Chen Zhiping, Lin Yaping. Information retrieval algorithm based on query expansion and classification [J]. Journal of System Simulation, 2006, 018 (007): 1926-1929, 1934.), etc. etc. These methods have verified the effectiveness of the retrieval method through experiments, but they have not completely solved the technical problems such as query topic drift and word mismatch in information retrieval.

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