• Korean Journal of Computational Design and Engineering
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• v.4 no.4
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• pp.285-294
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• 1999

This paper presents a content-search system built on distributed environments using the open product model of STEP, The content-search system searches design data for given product descriptions such as part name and features. Distribute object interfaces has been defined by IDL and distributed product data are searched through CORBA protocols. Web interfaces are also provided for interactive user interfaces. Given a user request, a mediator interacts with distributed search servers and sends collected results back to the user. The mediator has such metadata as location, program name, and other information about product data stored on distributed system. The search servers use SDAI interfaces to search STEP files or databases. The content-search system promotes the reuse of previous design within a company and the outsourcing of part designs.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.18-30
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• 2020

Recently, as graph-structured data is widely used in various fields such as social networks and semantic Webs, needs for an effective and efficient search on a large amount of graph data have been increasing. Previous keyword-based search methods often find results by considering only the relevance to a given query. However, they are likely to produce semantically similar results by selecting answers which have high query relevance but share the same content nodes. To improve the diversity of search results, we propose a top-k search method that finds a set of subtrees which are not only relevant but also diverse in terms of the content nodes by controlling their similarity. We define a criterion for a set of diverse answer trees and design two kinds of diversified top-k search algorithms which are based on incremental enumeration and A^⁎ heuristic search, respectively. We also suggest an improvement on the A^⁎ search algorithm to enhance its performance. We show by experiments using real data sets that the proposed heuristic search method can find relevant answers with diverse content nodes efficiently.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.229-238
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• 2007

This study was intended to point out the limit of existing digital content-centered studies, or approaches from the viewpoint of the supplier and in the aspect of business profit model and find ways to assess the quality of digital content, considering the characteristics of digital content. For this, the study is to apply value innovation strategy to digital content assessment, to analyze the applicability, and to propose a new and practical framework for digital content assessment method. To this end, this study selected the global No. 1 search service provider Google and local portal site Naver search service. The study on assessment factors by value innovation strategy was based on existing literature, while user-value elements in that respect were confined to information quality, interactivity, communication, interactive storytelling, and usability. This study objectified the relation with the value innovation strategic analysis, through qualitative and quantitative analyses on value elements of search service users.

• Journal of Korean Library and Information Science Society
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• v.10
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• pp.27-58
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• 1983

The purpose of this study is to clarify the educational literature search methodology objectives and the content structure of a course in bibliography. The content of this study can be summarized as follows: 1. The concept and domain of literature search methodology, which has traditionally gone by the name of a guide to use of literature and library, are described. 2. The need of incorporating the methodology into regular college curriculum was investigated in view of the ideology of college education. 3. The background, process, and current status of offering a course in the methodology as a part of regular college curriculum were examined. 4. The educational objective of a course in the methodology was set at the successful activities in self study, life-long-education, and special topic research. 5. Considering the fact that technical knowledge and propositional knowledge should be realized simultaneously, that educational experience should go hand in hand with materials and library, and that knowledge should be constructed systematically and logically, the content structure of the methodology were divided into the following six categories: a) the significance of the methodology of literature search b) the college library and the activities of literature search c) types and characteristics of materials d) literature search by catalog e) explanation of basic bibliography f) research and literature search

• Journal of Information Management
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• v.34 no.2
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• pp.55-66
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• 2003

The Web is rich with various sources of information. It contains the contents of documents, multimedia data, shopping materials and so on. Due to the massive and heterogeneous web document collections, users want to find various types of target pages. We can classify user queries as three categories according to users'intent, content search, the site search, and the service search. In this paper, we present that different strategies are needed to meet the need of a user. Also we show the properties of content information, link information and URL information according to the class of a user query. In the content search, content information showed the good result. However, we lost the performance by combining link information and URL information. In the site search, we could increase the performance by combining link information and URL information.

• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1878-1890
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• 2016

Web 2.0 has features produced the content through the user of the participation and share. The content production activities have became active since social network service appear. The social bookmark, one of social network service, is service that lets users to store useful content and share bookmarked contents between personal users. Unlike Internet search engines such as Google and Naver, the content stored on social bookmark is searched based on tag keyword information and unnecessary information can be excluded. Social bookmark can make users access to selected content. However, quick access to content that users want is difficult job because of the user of the participation and share. Our paper suggests a method recommending search word to be able to access quickly to content. A method is suggested by using Collaborative Filtering and Jaccard similarity coefficient. The performance of suggested system is verified with experiments that compare by 'Delicious' and "Feeltering' with our system.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.231-242
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• 1999

Generally, either caption-based search method or content-based search methods is used to retrieve video information. However, each search method has its limitations. Caption-based search is apt to lose consistency as for user's subjects, and content-based search is hard to extract general means. To enhance efficiency and correctness as for complementing each other, we propose the Integrated Video Data Model(IVDM) which integrates the two search methods, to device the model, we analyze video data and construct the structure of video information hierarchically. IVDM supports caption-based search as assigning meta-data by analyzing thematic-unit in the higher level, and also supports content-based search as extracting feature data by analyzing the content of video data in the lower level. We design Object-Oriented database schema of news video, based-on the IVDM. And we provide 4-type of queries and query processing algorithm to retrieve news video information.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.39-48
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• 2009

This study reviews the limit of image search by considering on the image search methods related to content-based image retrieval and suggests a user interface for more efficient content-based image retrieval and the ways to utilize image properties. For now, most studies on image search are being performed focusing on content-based image retrieval; they try to search based on the image's colors, texture, shapes, and the overall form of the image. However, the results are not satisfactory because there are various technological limits. Accordingly, this study suggests a new retrieval system which adapts content-based image retrieval and the conventional keyword search method. This is about a way to attribute properties to images using texts and a fast way to search images by expressing the attribute of images as keywords and utilizing them to search images. Also, the study focuses on a simulation for a user interface to make query language on the Internet and a search for clothes in an online shopping mall as an application of the retrieval system based on image attribute. This study will contribute to adding a new purchase pattern in online shopping malls and to the development of the area of similar image search.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.388-392
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• 2014

This paper proposes an early termination method of a block vector search for fast encoding of high efficiency video coding (HEVC) screen content coding (SCC). In the proposed algorithm, two blocks indicated by two block vector predictors (BVPs) were first employed as an intra block copy (IBC) search. If the sum of absolute difference (SAD) value of the block is less than a threshold defined empirically, an IBC BV search is terminated early. The initial threshold for early termination is derived by statistical analysis and it can be modified adaptively based on a quantization parameter (QP). The proposed algorithm is evaluated on SCM-2.0 under all intra (AI) coding configurations. Experimental results show that the proposed algorithm reduces IBC BV search time by 29.23% on average while the average BD-rate loss is 0.41% under the HEVC SCC common test conditions (CTC).

• The Journal of the Korea Contents Association
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• v.9 no.1
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• pp.30-44
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• 2009

In this paper, we propose the mobile P2P structure supporting content searches for mobile peers efficiently. The proposed mobile P2P structure is a 3-tier structure which consists of a mobile peer, a mobile super peer, and a stationary super peer to reduce the content search cost of mobile P2P service. For content searches, mobile peer searches content in the communication range and performs hierarchical content searches which is using mobile super peer, stationary super peer for expansion of query region. In order to support hierarchial content searches and the continuity of services according to peer mobilities, peer's join/leave processes are explicitly stored by supporting message structures to the upper layer It is shown through experimental evaluation that the proposed structure improves about 32% contents search performance over the existing 2-tier structure. Since it also reduces the messages transferred to the stationary super peers, it reduced about 25% search loads of them.