• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.793-806
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• 2002

Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

• Journal of Korean Society of Archives and Records Management
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• v.16 no.1
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• pp.175-193
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• 2016

A topic map was designed as an efficient information retrieval method that is optimized for classification, organization, and navigation through the use of a semantic link network above information resources. With this, this study aims to design a topic map-based university archives retrieval system to provide the relevant information retrieval. For this study, electronic records that relate to the academic administration within two years of D university were collected, and topic map editing was carried out with Ontopia Omnigator. Topics were classified according to their functional analysis of academic administration. In the end, the number of topics was finalized as 626, with 6 types in general: academic work, staff, college register, student, university, etc. Association was separated into six types as well, which were formed with consideration to the relationships among topics. In addition, there are seven occurrence types: register class, register number, register date, receiver, title, creator, and identifier. It is expected that the associative nature of the designed topic map-based retrieval system in this study will make navigation of large records easy and allow incidental discovery of knowledge.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.730-739
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• 2010

One of core technology in Web 2.0 is tagging, which is applied to multimedia data such as web document of blog, image and video etc widely. But unlike expectation that the tags will be reused in information retrieval and then maximize the retrieval efficiency, unacceptable retrieval results appear owing to toot limitation of tag. In this paper, in the base of preceding research about image retrieval through tag clustering, we design and implement a topic map generation system which is a semantic knowledge system. Finally, tag information in cluster were generated automatically with topics of topic map. The generated topics of topic map are endowed with mean relationship by use of WordNet. Also the topics are endowed with occurrence information suitable for topic pair, and then a topic map with semantic knowledge system can be generated. As the result, the topic map preposed in this paper can be used in not only user's information retrieval demand with semantic navigation but alse convenient and abundant information service.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.223-230
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• 2003

Feature-based similarity retrieval has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects (e 'g', documents, images, video, music score, etc.). For example, images are represented by their color histograms, texture vectors, and shape descriptors, and are usually high-dimensional data. The performance of conventional multidimensional data structures(e'g', R- Tree family, K-D-B tree, grid file, TV-tree) tends to deteriorate as the number of dimensions of feature vectors increases. The R＊-tree is the most successful variant of the R-tree. In this paper, we propose a SOM-based R＊-tree as a new indexing method for high-dimensional feature vectors.The SOM-based R＊-tree combines SOM and R＊-tree to achieve search performance more scalable to high dimensionalities. Self-Organizing Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two dimensional space. The mapping preserves the topology of the feature vectors. The map is called a topological of the feature map, and preserves the mutual relationship (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. A best-matching-image-list. (BMIL) holds similar images that are closest to each codebook vector. In a topological feature map, there are empty nodes in which no image is classified. When we build an R＊-tree, we use codebook vectors of topological feature map which eliminates the empty nodes that cause unnecessary disk access and degrade retrieval performance. We experimentally compare the retrieval time cost of a SOM-based R＊-tree with that of an SOM and an R＊-tree using color feature vectors extracted from 40, 000 images. The result show that the SOM-based R＊-tree outperforms both the SOM and R＊-tree due to the reduction of the number of nodes required to build R＊-tree and retrieval time cost.

• The Korean Journal of Archival Studies
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• no.19
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• pp.57-102
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• 2009

Recently, distribution of record via web and coefficient of utilization are increase. so, Archival information service using website becomes essential part of record center. The main point of archival information service by website is making record information retrieval easy. It has need of matching user's request and representation of record resources correctly to making archival information retrieval easy. Archivist and record manager have used various information representation tools from taxonomy to recent thesaurus, still, the accuracy of information retrieval has not solved. This study constructed record retrieval system based on Topic Map by modeling record resources which focusing on description metadata of the records to improve this problem. The target user of the system is general web users and its range is limited to the president related sources in the National Archives Portal Service. The procedure is as follows; 1) Design an ontology model for archival information service based on topic map which focusing on description metadata of the records. 2) Buildpractical record retrieval system with topic map that received information source list, which extracted from the National Archives Portal Service, by editor. 3) Check and assess features of record retrieval system based on topic map through user interface. Through the practice, relevance navigation to other record sources by semantic inference of description metadata is confirmed. And also, records could be built up as knowledge with result of scattered archival sources.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.467-468
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• 2014

본 논문에서는 파일 내용 기반 검색 프로그램을 설계하고 구현하였다. 역 인덱스 구조를 이용하여 설계하였으며 별도의 정보 검색 라이브러리 사용 없이 구현하였다. 인덱스 파일은 트라이 자료 구조를 직접 설계 및 구현 하였으며 자바 언어의 HashMap 구조를 중첩 형태로 구현하였다. 개발 시스템의 유용성을 테스트하기 위해 GRE 단어집에 수록된 약 3,300개의 단어를 사용하여 임의 생성한 텍스트 파일 집합을 사용하였다.

• Journal of information and communication convergence engineering
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• v.2 no.2
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• pp.123-127
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• 2004

The most popular technique for image retrieval in a heterogeneous collection of color images is the comparison of images based on their color histogram. The color histogram describes the distribution of colors in the color space of a color image. In the most image retrieval systems, the color histogram is used to compute similarities between the query image and all the images in a database. But, small changes in the resolution, scaling, and illumination may cause important modifications of the color histogram, and so two color images may be considered to be very different from each other even though they have completely related semantics. A new method of color feature representation based on the 3-dimensional RGB color map is proposed to improve the defects of the color histogram. The proposed method is based on the three 2-dimensional projection map evaluated by projecting the RGB color space on the RG, GB, and BR surfaces. The experimental results reveal that the proposed is less sensitive to small changes in the scene and that achieve higher retrieval performances than the traditional color histogram.

• Journal of the Korean Society for information Management
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• v.24 no.3
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• pp.321-341
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• 2007

It will be possible to prevent the infringement of the trademarks and the insueing disputes regarding the originality of the trademarks by using an efficient content-based trademark image retrieval system. In this paper, we describe a content-based image retrieval system using the Self Organizing Map(SOM) algorithm. The SOM algorithm utilizes the visual features, which were derived from the gray histogram representation of the images. In addition, we made the objective effectiveness evaluation possible by coming up with a quantitative measure to gauge the effectiveness of the content-based image retrieval system.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.9 no.2
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• pp.73-79
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• 2010

The most popular technique for image retrieval in a heterogeneous collection of color images is the comparison of images based on their color histogram. The color histogram describes the distribution of colors in the color space of a color image. In the most image retrieval systems, the color histogram is used to compute similarities between the query image and all the images in a database. But, small changes in the resolution, scaling, and illumination may cause important modifications of the color histogram, and so two color images may be considered to be very different from each other even though they have completely related semantics. A new method of color feature representation based on the 3-dimensional RGB color map is proposed to improve the defects of the color histogram. The proposed method is based on the three 2-dimensional projection map evaluated by projecting the RGB color space on the RG, GB, and BR surfaces. The experimental results reveal that the proposed is less sensitive to small changes in the scene and that achieve higher retrieval performances than the traditional color histogram.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.1
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• pp.69-77
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• 2000

In retrieving and analyzing digital map information using mouse or key strokes, it needs several times of repeated mouse operation for designating the range of study area. In this study, we proposed a voice activated map information retrieval system for eliminating such repetitions and we realized the system on the personal computer. The system was constructed in two ways - traditional OLE(object linking embedding) method and MFC(Microsoft fundamental class) method in controlling of window display for practical use. In the system performance evaluation, the retrieval data for digital map were consisted of 68 words uttered by 3 male persons which include attribute words and control words for Susung-gu area of Taegu city in a 1:5,000 map. As the results, we obtained the average 98.02% of recognition rate through on-line tests in the office environment and the operating speed of 5.39 seconds by OLE, 10.38 seconds by MFC. These results showed the possibility for practical use of information retrieval system using speech recognition in digital map.