Preference-based intelligent retrieval method and system

Abstract

The invention relates to the field of data retrieval, and discloses a preference-based intelligent retrieval method and system. The method includes the steps that a subject preference model of a user is established on the basis of subject classification of data, user characteristics and operation logs; query expansion is performed through the subject preference model of the user and retrieval input of the user to obtain a primary retrieval result; subject preference scoring is performed on the data through the subject preference model of the user and distribution conditions of the data on all subjects, and personalized retrieval ranking is preformed on the primary retrieval result on the basis of subject preference; secondary feedback retrieval is performed on the ranked primary retrieval result through a comprehensive model of relevance feedback and pseudo relevance feedback to obtain a final retrieval result. According to the method and system, subject distribution of data resources is determined through the subject indexing technology, retrieval vectors better representing user requirements are established through the query expansion based on subjects, relevance feedback and other technologies, and the retrieval result meeting potential requirements of the user better is provided for the user.

Description

technical field [0001] The invention relates to the field of data retrieval, in particular to a preference-based intelligent retrieval method and system. Background technique [0002] With the continuous improvement of social informatization and the rapid development of IT equipment, the storage capacity of information is increasing exponentially; at the same time, people's requirements for information acquisition are getting higher and higher. How to use retrieval technology to quickly find the useful information you need Information is getting harder and harder. Traditional search engines search based on keywords, but even if multiple keywords are used for combined search, the number of results obtained is still innumerable in the face of massive network information, and it is necessary to find the most needed information from these results It is also a tough job for the user. Therefore, the most critical problem of current data retrieval is how to find the information t...

AI Technical Summary

Problems solved by technology

However, the above method is mainly based on the descriptive information (combination of keywords, time, search scope, etc.) The information cannot reflect the differences among users. Even if the existing technology is used for optimization, the retrieval results are difficult to fully reflect the differences in the needs of different users, which makes it difficult to achieve the ideal retrieval efficiency, accuracy and user satisfaction in the existing methods. status

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