• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.60-69
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• 1996

To retrieve complex data such as images in multimedia information, we need the content-based retrieval methods based on the visual properties rather than keywords. In this paper, a contrent-based image retrieval system is desinged and implemented to retrieve images using the features of images such as colors, lines and intensity vetor features when a visual query inputs. The contents for image retrievals are the color features extracted from the color component of 16 blocks of the image, th eline features extracted form 4 lines in the image and the shape features extracted from the intensity vectors of the 16 blocks. We can either use a whole image or a sketch image for query. As the experimental results demonstrate the precision 91% the recall 33% and the average rank 3.1 the retrieval performance is found to be high. The experimental results indicate that the retrieval using the weighted features have led to substantial improvement in the percision and performance of system.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.240-246
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• 2003

In this paper, we propose the fast image retrieval method based on object regions using bidirectional round filter in the wavelet transform region. A conventional method that extracts feature vectors on the whole of subband is reduced retrieval efficiency, because of unnecessary background information. The proposed method that extracts feature vectors on the only object region of subband by using bidirectional round filter improve retrieval efficiency, because of removing of background information. And it certainly maintains retrieval efficiency in case of reduction of feature vectors according to color information. Consequently, the retrieval efficiency is improved with 2.5%∼5.3% values, which have a little changes according to characteristics of image.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.99-104
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• 2009

The SMS(Short Message Service) in Mobile phone is a service that a text message by 80byte is transmitted and received. Recently it's used instead of voice calls. In this paper, We investigate how you take advantage of the SMS for searching information without simply as a means of voice call, and how much efficiency does the SMS have in Location Information Retrieval Services on LBS(Location-based service). Based on the previous topics, we design the information retrieval system using SMS for solveing the rates issue by existing wireless Internet access, and propose the possibility as new forms of content services.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.2
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• pp.12-17
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• 2003

This paper proposes content-based image retrieval system with fuzzy ART neural network algorithm. Retrieving large database of image data, the clustering is essential for fast retrieval. However, it is difficult to cluster huge image data pertinently, Because current retrieval methods using similarities have several problems like low accuracy of retrieving and long retrieval time, a solution is necessary to complement these problems. This paper presents a content-based image retrieval system with neural network in order to reinforce abovementioned problems. The retrieval system using fuzzy ART algorithm normalizes color and texture as feature values of input data between 0 and 1, and then it runs after clustering the input data. The implemental result with 300 image data shows retrieval accuracy of approximately 87%.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.67-79
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• 2007

As the Web technologies and wired/wireless network are improved and various new multimedia services are introduced recently, need for searching multimedia including video data has been much increasing, The previous approaches for multimedia retrieval, however, do not make use of the relationships among semantic concepts contained in multimedia contents in an efficient way and provide only restricted search results, This paper proposes a multimedia retrieval system exploiting semantic relevancy of multimedia contents based on a domain ontology, We show the effectiveness of the proposed system by experiments on a prototype system we have developed. The proposed multimedia retrieval system can extend a given search keyword based on the relationships among the semantic concepts in the ontology and can find a wide range of multimedia contents having semantic relevancy to the input keyword. It also presents the results categorized by the semantic meaning and relevancy to the keyword derived from the ontology. Independency of domain ontology with respect to metadata on the multimedia contents is preserved in the proposed system architecture.

• Journal of Korea Multimedia Society
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• v.14 no.4
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• pp.567-576
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• 2011

In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.

• Journal of Korea Multimedia Society
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• v.7 no.9
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• pp.1219-1232
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• 2004

Recently, the web sites, such as e-business sites and shopping mall sites, deal with lots of catalog image information and contents. As a result, it is required to support semantic-based image retrieval efficiently on such image data. This paper presents a semantic-based image retrieval system, which adopts XML and Fuzzy technology. To support semantic-based retrieval on product catalog images containing multiple objects, we use a multi-level metadata structure which represents the product information and semantics of image data. To enable semantic-based retrieval on such image data, we design a XML database for storing the proposed metadata and study how to apply fuzzy data. This paper proposes a system, generate the fuzzy data automatically to use the image metadata, that can support semantic-based image retrieval by utilizing the generating fuzzy data. Therefore, it will contribute in improving the retrieval correctness and the user's satisfaction on semantic-based e-catalog image retrieval.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.494-506
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• 2003

Recently, explosive popularity of multimedia information has triggered the need for retrieving multimedia contents efficiently from the database including audio, video and images. In this paper, we propose an XML-based retrieval scheme and a data model that complement the weak aspects of annotation and conent based retrieval methods. The Property and hierarchy structure of image and video data are represented and manipulated based on the Multimedia Description Schema (MDS) that conforms to the MPEG-7 standard. For audio contents, pitch contours extracted from their acoustic features are converted into UDR string. Especially, to improve the retrieval performance, user's access pattern and frequency are utilized in the construction of an index. We have implemented a prototype system and evaluated its performance through various experiments.

• The Journal of the Korea Contents Association
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• v.7 no.7
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• pp.50-59
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• 2007

This paper describes a question analysis and expansion based on semantics for on efficient information retrieval. Results of all information retrieval systems include many non-relevant documents because the index cannot naturally reflect the contents of documents and because queries used in information retrieval systems cannot represent enough information in user's question. To solve this problem, we analyze user's question semantically, determine the answer type, and extract semantic features. And then we expand user's question using them and syntactic structures which are used to represent the answer. Our similarity is to rank documents which include expanded queries in high position. Especially, we found that an efficient document retrieval is possible by a question analysis and expansion based on semantics on natural language questions which are comparatively short but fully expressing the information demand of users.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.154-162
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• 2019

Despite the development of information and communication technology, which has a great impact on society and culture, there is no platform that provides a systematic classification and state-of-the-art information retrieval system on the traditional culture. Therefore, this paper developed a traditional culture retrieval system capable of convergence services with systematic classification and retrieval based on automatically generate and visualize the 3D timeline. This system provides the function of collecting traditional culture contents, classifying and storing collected traditional culture contents, and automatically generating 3D digital timeline based on stored traditional culture contents. In addition, a system satisfaction questionnaire was developed to evaluate the usability of the system, and 19 students participated in verifying the system. As a result of the experiment, the satisfaction of the system showed that all items were 'satisfied' on average.