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Text-based query expansion and sort method in image retrieval

A query expansion and image retrieval technology, applied in special data processing applications, instruments, electrical and digital data processing, etc., can solve problems such as image retrieval effects, and achieve the effects of low space-time cost, strong integrity, and good space-time efficiency

Inactive Publication Date: 2010-12-01
FUDAN UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

Although the text-based image retrieval technology is derived from the more mature text retrieval technology, there are some inapplicable technologies in it, which will have a negative impact on image retrieval.
The general query expansion model or ranking model cannot be effective for image retrieval, and the existing research on query expansion and retrieval document ranking mode for text retrieval needs to be strengthened and deepened

Method used

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  • Text-based query expansion and sort method in image retrieval
  • Text-based query expansion and sort method in image retrieval

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Embodiment 1

[0049] 1. Algorithm process framework

[0050] attached figure 1 It is a flow chart of the application framework, and numbers 1-4 respectively represent the above four main functional modules.

[0051] The framework is divided into four main modules: Pre-Processing and Pre-Analysis, Concept Semantic Relativity Measurement, Query Expansion based on Fusion of Expansion Rules ) and Retrieval ResultsRanking based on Scoring. Three of the four core algorithms, the English word semantic similarity measurement algorithm based on WordNet, the Chinese word semantic similarity measurement algorithm based on HowNet, and the retrieval result scoring and optimization algorithm will be used in the scoring-based retrieval result sorting module, The query expansion word selection and optimization algorithm based on the expansion rules will be used in the query expansion module that fuses the expansion rules. In the first two modules of the application framework, some existing technologies ...

Embodiment 2

[0158] Embodiment 2 application example

[0159] attached figure 2 It demonstrates the specific steps of the above-mentioned algorithm flow framework through a specific example, and gives people an intuitive understanding by giving the intermediate output of each algorithm module and the final retrieval result of the framework.

[0160] Labels (1) and (2) are the original English query and Chinese query input by the user respectively; labels (3) and (4) respectively use the English semantic dictionary WordNet and the Chinese semantic dictionary HowNet, using the "extension rule-based query The expanded word sets corresponding to the original English query and Chinese query obtained by the "Extended Word Selection and Optimization Algorithm"; labels (5) and (6) are the expanded word sets based on the original English query and Chinese query, respectively, using the image search engine The corresponding retrieval results obtained; labels (7) and (8) are the initial retrieval l...

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Abstract

The invention belongs to the field of multimedia information retrieval and relates to a method for realizing thesaurus-based query expansion and sort in image retrieval. The method comprises a WordNet-based English word semantic similarity metric algorithm, a HowNet-based Chinese word semantic similarity metric algorithm, an expansion rule-based query expansion word selection and optimization algorithm and a retrieval result evaluation and optimization algorithm. In the method, an image search engine is improved by the relevant text processing method and the relevant semantic network dictionary; and the retrieval result is sorted through semantic expansion, user interaction and improved similarity measurement. Compared with the traditional method, the method has the advantages of high accuracy rate, high integrality and low space-time cost. The method has very important significance for performing high-efficiency image retrieval according to image high-layer semantic information and on the basis of a large-scale image data set, and has wide application value in the field of cross-linguistic and cross-media retrieval.

Description

technical field [0001] The invention belongs to the field of multimedia information retrieval, relates to a specific media-image retrieval method, in particular to a method for realizing query expansion and sorting based on a semantic dictionary in image retrieval. The method can be used to cooperate with the content-based image retrieval method to improve image search quality and user search experience. Background technique [0002] In recent years, with the development of the Internet and social informatization, the capacity of digital images is increasing rapidly, and a large amount of image data is generated every day. How to quickly and accurately find, access images, and effectively use these images has become an urgent problem to be solved, which is the so-called image retrieval technology. The earliest text-based image retrieval technology (Text-based Image Retrieval, TBIR) was mainly used; since the 1990s, the research and application of content-based image retriev...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 张玥杰金城薛向阳岑磊彭琳
Owner FUDAN UNIV
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