• Journal of the Korea Society of Computer and Information
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• v.9 no.2
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• pp.19-26
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• 2004

This paper proposes ACA (Adaptive Component Analysis) as a method for feature extraction and analysis of the content-based image retrieval system. For satisfactory retrieval, the features extracted from images should be appropriately applied according to the image domains and for this, retrieval measurement is proposed in this study. Retrieval measurement is a standard indicating how important the value of a relevant feature is to image retrieval. ACA is a middle stage for content-based image retrieval and it purposes to improve the retrieval speed and performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.3
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• pp.150-170
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• 2008

In recent years, main focus of research on image retrieval techniques is on content-based image retrieval. Text-based image retrieval schemes, on the other hand, provide semantic support and efficient retrieval of matching images. In this paper, based on Formal Concept Analysis (FCA), we propose a new image indexing and retrieval technique. The proposed scheme uses keywords and textual annotations and provides semantic support with fast retrieval of images. Retrieval efficiency in this scheme is independent of the number of images in the database and depends only on the number of attributes. This scheme provides dynamic support for addition of new images in the database and can be adopted to find images with any number of matching attributes.

• KSCI Review
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• v.12 no.1
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• pp.9-19
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• 2004

This paper proposes ACA (Adaptive Component Analysis) as a method for feature extraction and analysis of the content-based image retrieval system. For satisfactory retrieval, the features extracted from images should be appropriately applied according to the image domains and for this. retrieval measurement is Proposed in this study. Retrieval measurement is a standard indicating how important the value of a relevant feature is to image retrieval ACA is a middle stage for content-based image retrieval and it purposes to improve the retrieval speed and performance.

• Korean Journal of Cognitive Science
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• v.34 no.1
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• pp.21-38
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• 2023

The present study was designed to investigate the effect of the difficulty level of retrieval practice and the association strength of categories and stimuli within categories on memory inhibition. Most of the studies have investigated whether inhibition was occurred by manipulating the degree of association strength, emotion value or physical characteristics of non-retrieval practice words within the retrieval practice category. Therefore, it was necessary to study how inhibition occurs according to the degree of difficulty of retrieval stimuli during retrieval practice. The difficulty of retrieval was manipulated into three levels: difficult condition, normal condition, and easy condition through the degree of presentation of consonants and vowels of words during retrieval learning. Additionally, the strength of association between categories and words within categories was manipulated. In previous studies, retrieval-induced forgetting occurred under conditions where the association strength between categories and words within the categories was strong. On the other hand, retrieval-induced forgetting did not occur under conditions where the association strength between categories and words within the categories was weak. The present study, if the inhibition process differs according to the difficulty of retrieval, the possibility of different results from previous studies was explored according to the difference in the strength of association with the category. As a result of the study, in the condition of strong association strength, retrieval-induced forgetting was observed under normal and difficult retrieval difficulty conditions. Whereas retrieval-induced forgetting was not observed under conditions of easy retrieval difficulty condition. In the condition of weak association strength, retrieval-induced forgetting tended to occur under difficult retrieval difficulty conditions. Whereas retrieval-induced forgetting was not observed under conditions of normal and easy retrieval difficulty condition. These results suggest that memory inhibition may appear differently depending on the difficulty of retrieval.

• Asia pacific journal of information systems
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• v.2 no.1
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• pp.3-15
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• 1992

This paper proposes a new referential model for data retrieval as an alternative to exact matching. While exact matching is an effective data retrieval model, it is based on fairly strict assumptions and limits our capabilities in data retrieval. This study redefines data retrieval to include non-binary data retrieval in addition to binary data retrieval, proposes Double Anchor Preference Model (DAPM), and analyzes its logical charateristics. DAPM supports non-binary data retrieval. Further, it produces the same result as exact matching for the conventional binary data retrieval. These findings show that, at the logical level, the proposed DAPM retains all the desirable features for data retrieval.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1129-1133
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• 2006

In this thesis, we propose a semantics-based video retrieval system which supports semantics-retrieval for various users of massive video data. Proposed system automatically processes the extraction of contents information which video data has and retrieval process using agent which integrate annotation-based retrieval and feature-based retrieval. From experiment, the designed and implemented system shows increase of recall rate and precision rate for video data scene retrieval in performance assessment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.85-90
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• 2006

In this paper, we propose the content-based music information retrieval system with improved retrieval speed and stable performance while maintaining resonable retrieval accuracy In order to solve the in-stable system problem multi-feature clustering (MFC) is used to setup robust music DB. In addition, the music retrieval speed was improved by using the Superclass concept. Effectiveness of the system with SuperClass and without SuperClass is compared in terms of retrieval speed, accuracy and retrieval precision. It is demonstrated that the use of WC and Superclass substantially improves music retrieval speed up to $20\%\~40\%$ while maintaining almost equal retrieval accuracy.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.324-328
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• 2012

With the recent advances in information retrieval, cross-media retrieval has been attracting lot of attention, but several issues remain problems such as constructing effective correlations, calculating similarity between different kinds of media objects. To gain better cross-media retrieval performance, it is crucial to mine the semantic correlations among the heterogeneous multimedia data. This paper introduces a new method for cross-media retrieval which uses ontology to organize different media objects. The experiment results show that the proposed method is effective in cross-media retrieval.

• Journal of Information Processing Systems
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• v.9 no.3
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• pp.349-364
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• 2013

The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.

• Journal of the Korean Society for information Management
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• v.15 no.1
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• pp.129-148
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• 1998

The objective of this study is to develop a useful relevance feedback retrieval technique that can be applied to the current Boolean retrieval system. A feedback retrieval technique based on user model is recommended here to achieve this objective. To prove the usefulness of this feedback retrieval technique, two enhanced Boolean retrieval models including DNF model and P-norm model were evaluated first through retrieval effectiveness experiments. After selecting DNF model as the retrieval model, two feedback retrieval experiments were performed using initial and extended user models. It is proved that the feedback retrieval based on user model can greatly enhance the effectiveness of a Boolean retrieval system with a small modification.