• Journal of the Korean Society for Library and Information Science
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• v.16
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• pp.177-205
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• 1989

Retrieval effectiveness is the principal criteria for measuring the performance of an information retrieval system. This paper deals with the characteristics of 'relevance' of information and various measuring techniques of retrieval effectivess. The outlines of this study are as follows: 1) Relevance decision for evaluation should be devided into the user-oriented and the system-oriented decisions. 2) The recall-precision measure seems to be user-oriented, and the recall-fallout measure to be system-oriented. 3) Many of composite measures can not be justified III any rational manner unfortunately. 4) The Swets model has demonstrated that it yields, in general, a straight line instead of a curve of varying curvature and emphasized the fundamentally probabilistic nature of information retrieval. 5) The Cooper model seems to be a good substitute for precision and a useful measure for systems which ranked documents. 6) The Rocchio model were proposed for the evaluation of retreval systems which ranked documents, and were designed to be independent of cut-off. 7) The Cawkell model suggested that the Shannon's equation for entropy can be applied to measuring of retrieval effectiveness.

• 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 Library and Information Science
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• v.50 no.1
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• pp.417-435
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• 2016

Relevance judgment is important in terms of improving the effectiveness of information retrieval systems, and it has been dominant for users to search and use images utilizing internet and digital technologies. However, in the field of image retrieval, there have been only a few studies in terms of identifying relevance criteria. The purpose of this study aims to identify and characterize the non-relevance criteria from the failed image searches. In order to achieve the purpose of this study, a total of 135 participants were recruited and a total of 1,452 criteria items were collected for this study. Analyses and identification on the data set found thirteen criteria such as 'topicality', 'visual content', 'accuracy', 'visual feature', 'completeness', 'appeal to user', 'focal point', 'bibliographic information', 'impression', 'posture', 'face feature', 'novelty', and 'time frame'. Among these criteria, 'visual content' and 'focal point' were introduced in this current study, while 'action' criterion identified in previous studies was not shown in this current study. When image needs and image uses are analyzed with these criteria, there are distinctive differences depending on different image needs and uses.

• Journal of the Korean Society for information Management
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• v.10 no.2
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• pp.43-67
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• 1993

The primary purpose of the study is to improve the low preclslon often found In full-text retrleval systems. In order to enhance the low precision of full-text retrleval wh~le retaining ~ t s hgh recall, relevance feedback mechanisms based on probabilistic retrieval models (binary independence and two-Polsson Independence models) were employed. Thls paper investigates the effect of relevance feedback on the performance of full-text retrieval systems.

• ETRI Journal
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• v.33 no.2
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• pp.240-250
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• 2011

To enable a relevance feedback paradigm to evolve itself by users' feedback, a reinforcement learning method is proposed. The feature space of the medical images is partitioned into positive and negative hypercubes by the system. Each hypercube constitutes an individual in a genetic algorithm infrastructure. The rules take recombination and mutation operators to make new rules for better exploring the feature space. The effectiveness of the rules is checked by a scoring method by which the ineffective rules will be omitted gradually and the effective ones survive. Our experiments on a set of 10,004 images from the IRMA database show that the proposed approach can better describe the semantic content of images for image retrieval with respect to other existing approaches in the literature.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.669-672
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• 2001

We propose an efficient algorithm for an interactive content-based image retrieval using relevance feedback. In the proposed algorithm, a new query feature vector first is yielded from the average feature vector of the relevant images that is fed back from the result images of the previous retrieval. Each component weight of a feature vector is computed from an inverse of standard deviation for each component of the relevant images. The updated feature vector of the query and the component weights are used in the iterative retrieval process. In addition, the irrelevant images are excluded from object images in the next iteration to obtain additional performance improvement. In order to evaluate the retrieval performance of the proposed method, we experiment for three image databases, that is, Corel, Vistex, and Ultra databases. We have chosen wavelet moments, BDIP and BVLC, and MFS as features representing the visual content of an image. The experimental results show that the proposed method yields large precision improvement.

• Journal of Broadcast Engineering
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• v.5 no.1
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• pp.61-67
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• 2000

Generally, relevance, feedback reflecting user's intention has been used to refine the refine the query conditions in image retrieval. However, in this paper, the usage of the relevance feedback is extended to the image database categorization so as to be accommodated to the user independent image retrieval. In our approach, to guarantee a desirable user-satisfactory performance descriptors and the elements of the descriptors corresponding unique features associatiated with of each image are weighted using the relevance feedback where experts can more lead rather than beginners do. In this paper, we propose a proper image description scheme consisting of global information, local information, descriptor weights and element weights based on color and texture descriptors. In addition, we also introduce an appropriate learning method based on the reliability scheme preventing wrong learning from abusive feedback.

• 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.39-44
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• 2006

In this paper, search result list synthesis method is proposed using borda count method for still image retrieval based on MPEG-7 descriptors. MPEG-7 standardizes descriptors that extract feature information from media data. In many cases, using a single descriptor lacks of correctness, it is suggested to use multiple descriptors to enhance retrieval efficiency. In this paper, retrieval efficiency enhancement is achieved by combining multiple search results which are from each descriptor. In combining search result, newly calculated borda count method is proposed. Comparing current frequency compensated calculation, rank considered frequency compensation is used to score animage in database. This combining method is considered in Content based image retrieval system with relevance feedback algorithm which uses high level information from system user. In each relevance iteration step, adoptive borda count method is used to calculate score of images.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.141-152
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• 2005

A new emotion-based image retrieval method is proposed in this paper. Query emotion descriptors called query color code and query gray code are designed based on the human evaluation on 13 emotions('like', 'beautiful', 'natural', 'dynamic', 'warm', 'gay', 'cheerful', 'unstable', 'light' 'strong', 'gaudy' 'hard', 'heavy') when 30 random patterns with different color, intensity, and dot sizes are presented. For emotion image retrieval, once a query emotion is selected, associated query color code and query gray code are selected. Next, DB color code and DB gray code that capture color and, intensify and dot size are extracted in each database image and a matching process between two color codes and between two gray codes are peformed to retrieve relevant emotion images. Also, a new relevance feedback method is proposed. The method incorporates human intention in the retrieval process by dynamically updating weights of the query and DB color codes and weights of an intra query color code. For the experiments over 450 images, the number of positive images was higher than that of negative images at the initial query and increased according to the relevance feedback.

• Journal of the Korean Society for information Management
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• v.11 no.1
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• pp.31-56
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• 1994

To evaluate the retrieval effectiveness of the B03lean Request Conversion Mod4 the Relevance Weighted Boolean Model, and the P-NORM Model, the present study has been done with expenmental tests. It is proven that the Relevance Weighted Bdean Model is more effective in precision and the document output ranks than the other ones. The expenmental results indmte a promisii application of relevance mformation and weigh- schemes.