• Journal of Digital Convergence
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• v.10 no.9
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• pp.339-344
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• 2012

Established continuous vocabulary recognition system improved recognition rate by using decision tree based tying modeling method. However, since system model cannot support the retrieve of phoneme data, it is hard to secure the accuracy. In order to improve this problem, we remodeled a system that could retrieve probabilistic model from continuous vocabulary clustering model to phoneme unit. Therefore in this paper showed 95.88%of recognition rate in system performance.

• Journal of Korea Multimedia Society
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• v.8 no.8
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• pp.1032-1041
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• 2005

Now a days, PACS and the other image sharing systems use only high-level metadata for hospital to retrieve images. So if you want to retrieve some images, you have to know exact information about the patient. In this paper, we developed a Image Retrieval System based on MPEG-7 to retrieve medical images more efficiently. This system offers keyword retrieval using high-level metadata based of DICOM and similarity retrieval using low-level metadata based on MFEG-7. And we integrated high-level metadata and low-level metadata to retrieve medical images more exactly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.630-636
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• 2004

According to the increase of audio and video data utilization, the presentation of multimedia data contents and the work of retrieving, storing and manipulating a multimedia data have been the focus of recent work. The display for multimedia data should retrieve and access the contents easily that users want to present. This study is about the design and implementation of a system to retrieve multimedia data based on the contents of documentation or the caption information of a multimedia data for retrieving documentation including multimedia data. It intends to develop an filtering step to retrieve all of keyword within the caption information of multimedia data and text of a documentation. Also, the system is designed to retrieve a large amount of data quickly using an inverted file structure available for B+ tree.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.586-593
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• 2009

As most of the data configuration at distributed environment has a tree structure following the hierarchical classification, relative data retrieve is limited. Among these data, the data stored in a database has a problem in integration and efficient retrieve. Accordingly, we suggest the system that uses XMDR for distributed database integration and links XMDR to TopicMap for efficient retrieve of knowledge expressed hierarchically. We proposes a plan for efficient integration retrieve through using the XMDR which is composed of Meta Semantic Ontology, Instance Semantic Ontology and meta location, solves data heterogeneity and metadata heterogeneity problem and integrates them, and replaces the occurrence of the TopicMap with the Meta Location of the XMDR, which expresses the resource location of TopicMap by linking Meta Semantic Ontology and Instance Semantic Ontology of XMDR to the TopicMap.

• Journal of the Korean Society for information Management
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• v.16 no.4
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• pp.75-94
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• 1999

Indexing is a prerequisite function for the information retrieval system in order to retrieve the information of the documents effectively which are saved in database. As a digital data increases in accordance with the development of a computer, the numbers of literatures to be saved in database have also been increased in a large volume. To retrieve such documents of large volume, a lot of system resources and processing time will be required. In this paper, we suggest a advanced indexing method using text partition. This method can retrieve the documents of large volume in short processing time. We applied this suggested indexing method to real information retrieval system, and proved its excellent functions through the demonstration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.580-592
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• 1997

Since an ATM network consists of a number of VPC/VCC requiring various QoS requirements, the end-to-end QoS for each VPC/VCC should be guaranteed. Although many research works on the traffic control are under study to guarantee the QoS, there have been research efforts to reflect the results of network management functions into the traffic control mechanism. To effectively make use of the performance management functions into the VPC/VCC management, threre is a need for the network manager to rapidly retrieve the relevant information. In this research, the mechanism to effectively retrieve the management information using SNMP is suggested. First of all, we construct the MIBs in the agent for the corresponding VPC/VCC. Also, we suggest the way to retrieve MIB with minimum cost. Mathematical analysis shows that the proposed technique has better performance than that using the existing SNMP.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.187-194
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• 1999

Case-Based Reasoning(CBR) systems support ill structured decision-making. The measure of the success of a CBR system depends on its ability to retrieve the most relevant previous cases in support of the solution of a new case. One of the methodologies widely used in existing CBR systems to retrieve previous cases is that of the Nearest Neighbor(NN) matching function. The NN matching function is based on assumptions of the independence of attributes in previous case and the availability of rules and procedures for matching.(omitted)

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.134-137
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• 2003

Both browsing and retrieval with search engines are major operations that establish the interaction between users and the Web. Although both operations are usually combined to locate information from the Web, recent growth of the Web has overtaken the potential of this conventional interaction. This paper proposes the concept of Retrieve, Browse, and Analyze (RBA)-based interactions, as the improvement of the conventional Retrieve and Browse (RB)-based interaction. The prototype interface based on RBA-based interaction is also presented.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.810-813
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• 2004

Indexing and Retrieving images from large and varied collections using image content as a key is a challenging and important problem in computer vision application. In this paper, a color Content-based Image Retrieval (CBIR) system using hierarchical Region of Interest (ROI) query and indexing is presented. During indexing process, First, The ROIs on every image in the image database are extracted using a region-based image segmentation technique, The JSEG approach is selected to handle this problem in order to create color-texture regions. Then, Color features in form of histogram and correlogram are then extracted from each segmented regions. Finally, The features are stored in the database as the key to retrieve the relevant images. As in the retrieval system, users are allowed to select ROI directly over the sample or user's submission image and the query process then focuses on the content of the selected ROI in order to find those images containing similar regions from the database. The hierarchical region-of-interest query is performed to retrieve the similar images. Two-level search is exploited in this paper. In the first level, the most important regions, usually the large regions at the center of user's query, are used to retrieve images having similar regions using static search. This ensures that we can retrieve all the images having the most important regions. In the second level, all the remaining regions in user's query are used to search from all the retrieved images obtained from the first level. The experimental results using the indexing technique show good retrieval performance over a variety of image collections, also great reduction in the amount of searching time.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.384-389
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• 2008

Recently, the necessity of systems which effectively store and retrieve video data has increased. Conventional video retrieval systems retrieve data using menus or text based keywords. Due to the lack of information, many video clips are simultaneously searched, and the user must have a certain level of knowledge to utilize the system. In this paper, we suggest a natural language based conversational video retrieval system that reflects users' intentions and includes more information than keyword based queries. This system can also retrieve from events or people to their movements. First, an event database is constructed based on meta-data which are generated by domain analysis for collected video in an office environment. Then, a script database is also constructed based on the query pre-processing and analysis. From that, a method to retrieve a video through a matching technique between natural language queries and answers is suggested and validated through performance and process evaluation for 10 users The natural language based retrieval system has shown its better efficiency in performance and user satisfaction than the menu based retrieval system.