• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.579-586
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• 2002

The edge descriptor proposed by MPEG-7 standard is a representative approach for the contents-based image retrieval using the edge information. In the edge descriptor, the edge information is the edge histogram derived from a gray-level value image. This paper proposes a new method which extracts color edge information from color images and a new approach for the contents-based image retrieval based on the color edge histogram. The poposed method and technique are applied to image retrieval of the e-catalogue. For the evaluation, the results of image retrieval using the proposed approach are compared with those of image retrieval using the edge descriptor by MPEG-7 and the statistics shows the efficiency of the proposed method. The proposed color edge model is made by combining the R,G,B channel components vectorially and by characterizing the vector norm of the edge map. The color edge histogram using the direction of the color edge model is subsequently used for the contents-based image retrieval.

• Journal of Information Science Theory and Practice
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• v.1 no.3
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• pp.33-46
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• 2013

Despite limited success, today's information retrieval (IR) systems are not intelligent or reliable. IR systems return poor search results when users formulate their information needs into incomplete or ambiguous queries (i.e., weak queries). Therefore, one of the main challenges in modern IR research is to provide consistent results across all queries by improving the performance on weak queries. However, existing IR approaches such as query expansion are not overly effective because they make little effort to analyze and exploit the meanings of the queries. Furthermore, word sense disambiguation approaches, which rely on textual context, are ineffective against weak queries that are typically short. Motivated by the demand for a robust IR system that can consistently provide highly accurate results, the proposed study implemented a novel topic detection that leveraged both the language model and structural knowledge of Wikipedia and systematically evaluated the effect of query disambiguation and topic-based retrieval approaches on TREC collections. The results not only confirm the effectiveness of the proposed topic detection and topic-based retrieval approaches but also demonstrate that query disambiguation does not improve IR as expected.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1498-1504
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• 2016

The progress of mobile computing technology is bringing a large amount of multimedia contents such as image. Thus, we need an image retrieval system which searches semantically relevant image. In this paper, we propose a semantic image annotation and retrieval in mobile environments. Previous mobile-based annotation approaches cannot fully express the semantics of image due to the limitation of current form (i.e., keyword tagging). Our approach allows mobile devices to annotate the image automatically using the context-aware information such as temporal and spatial data. In addition, since we annotate the image using RDF(Resource Description Framework) model, we are able to query SPARQL for semantic image retrieval. Our system implemented in android environment shows that it can more fully represent the semantics of image and retrieve the images semantically comparing with other image annotation systems.

• Journal of the Korean Society for Library and Information Science
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• v.27
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• pp.265-289
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• 1994

Databases publicly available for online searching permit both citation and subject searching, however, subject searching has dominated the online search environment. Despite the power of citation searching, it may be underutilized This study explored the relationship between the number of cited references used in a citation search and information retrieval effectiveness, a relatively unstudied phenomenon. Three articles in the library and information science literature were chosen to represent sample questions. Cited reference searches were conducted for each article and each of its references. All searches were conducted in Social Scisearch and Scisearch on DIALOG. Relevance judgments on the retrieved citations were obtained from the authors of the original articles. This research focused on analyzing, in terms of information retrieval effectiveness, the overlap among postings sets retrieved by various combinations of cited references. The findings from the three case studies clearly showed that the more cited references used for the citation search, the better the performance, in terms of retrieving more relevant documents, up to a point of diminishing retums. In addition, generally the overall level of overlap among relevant documents sets was found to be low. Therefore, if only some of the cited references among many candidates are used for a citation search, a significant proportion of relevant documents may be missed. The analysis of the characteristics of cited references provided the ways to predict which cited refereces would be useful to improve information retrieval. The findings of this comprehensive exploratory study are of interest for both theoretical and practical reasons. They contribute to the development of a theoretical model for the effective use of the citation search. This model might also be implemented in operational online systems. In addition, the findings potentially will help online searchers improve their search strategies using the citation search so that they can better achieve their information retrieval goals: the retrieval of items relevant to a given question and the suppression of nonrelevant items.

• The Journal of Society for e-Business Studies
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• v.7 no.2
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• pp.21-38
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• 2002

Document retrieval (DR) has been a serious issue for long in the field of Office Information Management. Nowadays, our daily work is becoming heavily dependent on the usage of information collected from the internet, and the DR methods on the Web has become an important issue which is studied more than any other topic by many researchers. The main purpose of this study is to develop a model to manage business documents by integrating three major methodologies used in the field of electronic library and information retrieval: Metadata, Thesaurus, and Index/Reversed Index. In addition, we have added a new concept of eDocument, which consists of metadata about unit documents and/or unit document themselves. eDocument is introduced as a way to utilize existing document sources. The core concepts and structures of the model were introduced, and the architecture of the eDocument management system has been proposed. Test (simulation) result of the model and the direction for the future studies were also mentioned.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1424-1440
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• 2015

It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

• Journal of the Korean Society for information Management
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• v.13 no.2
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• pp.223-242
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• 1996

This study proposes an integration model of information retrieval systems using a standard distributed object computing technology in digital library environments. In the proposed integration model called DDIRIORB, the middleware broker based on CORBA is designed for the transparent access to the distributed information repositories and the consistent view of the information retrieval by applying 239.50 protocol. The DDIRIORB is an adaptable open architecture that allows for the following benefits : bibliographic and abstract information retrieval simultaneously, interoperability between application servers and clients, consistent view of search results, complexity reduction of integration interfaces, and easy to use.

• Journal of Korean Library and Information Science Society
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• v.35 no.3
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• pp.271-291
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• 2004

Such information services source like digital library has been asked information services of atypical multimedia database like image, voice, VOD/AOD. Examined in this study are suggestions such as word-phrase generator, syllable recoverer, morphological analyzer, corrector for voice processing. Suggested voice processing technique transform voice database into tort database, then extract index database from text database. On top of this, the study suggest a information retrieval model to use in extracted index database, voice full-text information retrieval.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.375-378
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• 2000

In this paper, we propose a novo] content-based image retrieval system using both Hidden Markov Model(HMM) and an improved chain code. The Gaussian Mixture Model(GMM) is applied to statistically model a color information of the image, and Deterministic Annealing EM(DAEM) algorithm is employed to estimate the parameters of GMM. This result is used to segment the given image. We use an improved chain code, which is invariant to rotation, translation and scale, to extract the feature vectors of the shape for each image in the database. These are stored together in the database with each HMM whose parameters (A, B, $\pi$) are estimated by Baum-Welch algorithm. With respect to feature vector obtained in the same way from the query image, a occurring probability of each image is computed by using the forward algorithm of HMM. We use these probabilities for the image retrieval and present the highest similarity images based on these probabilities.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.442-445
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• 2005

It constructs a database generally and service it does, to use a commercial business DBMS that manages information and to use a retrieval system that supports a search, it adopts the gearing method of the DBMS and information retrieval system. But like this method is inconvenient must operate the DBMS and information retrieval system with duplication to be, there is a weak point where the data management and processing become accomplished with duplication. It presents the DB construction and information search and the management model of the KRISTAL-2002 information retrieval and management system base for the scientific and technical information data management and processing from the dissertation which it sees.