• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.414-422
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• 2011

IR (Information Retrieval) systems have the methods that compare relationships between query and index to identify document that may be fit to the user's query keyword. However, the methods usually ignore the importance of relations that are not expressed in the query. Therefore, in this study, we describe how to refine the queries' relation from keyword and to reveal the hidden intent. A useful relationship between query and keyword in IR wth studied and we classified the tion fromrelation. Firstfromall, we did researchmrelated on semantic relationship and ontolhiical researchmin foreign and domestic research, and also analyzed semantic network practices, information retrieval technolhiy, extracted and classified the tion fromrelationships s' relasite's real-world datamin whichminformation retrieval technolhiin fare applied. Next, we souiht to solve the problems occurred frequently i' relasituation that searchers tioically face. I' relacurrent search technolhiy, the mesh searchmresult fare poured by simply comparn ina query with index terms. Therefore, the need for an intelligent search fittn inusers' intent is required. The relationships between two queries to re hiddee and identify relasearcher's intent have to be revealed. By analyzn inthe practical cthes s' queries and classifyn inthem into nine kind fromrelationship tion, we proposed the method to design relation revealn inand role namn i, and we have also illustrated limitations of that methods.

• Korean Journal of Cognitive Science
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• v.10 no.1
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• pp.67-78
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• 1999

Information providers on WWW have been rapidly increasing, and they provide a vast amount of information in various fields, Because of this reason, it becomes hard for users to get the information they want. Although there are several search engines that help users with the keyword matching methods, it is not easy to find suitable keywords. In order to solve these problems with a specific domain, we propose an intelligent information agent(HHA-la : HongIk Information Agent) that converts user's q queries to forms including related domain words in order to represent user's intention as much as it can and provides the necessary information of the domain to users. HHA-la h has an ontological knowledge base of animal domain, supplies necessary information for queries from users and other agents, and provides relevant web page information. One of system components is a WebDB which indexes web pages relevant to the animal domain. The system also supplies new operators by which users can represent their thought more clearly, and has a learning mechanism using accumulated results and user feedback to behave more intelligently, We implement the system and show the effectiveness of the information agent by presenting experiment results in this paper.

• Archives of design research
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• v.19 no.2 s.64
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• pp.313-322
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• 2006

In this paper, we introduce 'Contents Based Image Retrieval' which helps a user find the images he or she needs more easily and reconfigures the images automatically. With this system, we try to realize the language of (motion) picture, that is, the Montage from the viewpoint of the user. The Real-time Montage System introduced in this paper uses 'Discrete Fourier Transform'. Through this, the user can find the feature of the image selected and compare the analogousness with the image in the database. This kind of system leads to the user's speedy and effective retrieving, Also, we can acquire the movement image of the user by Camera Tracking in Real-time. The movement image acquired is to be reconfigured automatically with the image of the user. In this way, we can get an easy and speedy image reconfiguration which sets to the user's intention. This system is a New Media Design tool(entertainment) which induces a user enjoy participating in it. In this system, Thus, the user is not just a passive consumer of one-way image channels but an active subject of image reproduction in this system. It is expected to be a foundation for a new style of user-centered movie (media based entertainment).

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.551-553
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• 1999

최근에는 기하학적인 www의 성장과 더불어 인터넷 서비스를 통한 정보 획득과 고유, 교환 및 원격 시스템 접속을 통한 인터넷 응용 처리 서비스에 대한 연구가 많이 이루어지고 있다. 그리고 이를 기반으로 소프트웨어 생산성과 품질 향상을 위한 재사용을 이루기 위해 명확한 해결책으로 설계 패턴 재사용이 제시되었다. 그러므로 이들 설계 패턴을 웹을 기반으로 다수의 사용자가 융통성 있는 시스템 구축시 필요로 하는 패턴을 공유할 수 있는 적절한 설계 패턴 라이브러리 시스템이 요구되어졌다. 이는 웹 상에서 설계 패턴의 효율적인 검색과 의도된 패턴의 생성을 재사용 가능하도록 패턴 구조를 다운로드하고 보다 도메인 한정적인 응용 생산을 지원하고자 한다. 따라서 본 논문에서는 웹 상에서 설계 패턴 라이브러리를 ASP(Active Server Page)를 이용하여 구현하였다. 본 시스템을 통해 설계 패턴 재사용자들은 패턴을 등록, 수정, 삭제하고 또한 패턴을 대화적으로 검색하고 이해하며, 구조를 다운 받을 수 있다. 따라서 애플리케이션 시스템 구축에서 설계 패턴 사용자의 효율적인 방법을 제공한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.772-774
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• 2017

Currently, there are many simple searches for local culture and tourism, but systematic information retrieval using ontology technology is weak. The keyword-based search, which is an existing search method, derives a search result that is different from a user's wanted intention. On the other hand, semantic search using ontology constructs shows the information related to the search term by creating a relation between words and words. Therefore, when tourists search for cultural and tourist attractions in the area, they provide information that includes meaning relevance in the search results. If the ontology provides information on the culture, sightseeing area, transportation, Can be more easily grasped. In this paper, we propose an ontology-based retrieval system based on culture and tourist sites utilizing public institutions database by using mobile application by extending search system which relied only on existing internal database to provide accurate and reliable information to users. This efficient structure of the ontology makes it possible to provide information suitable for the user quickly and accurately.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.169-180
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• 2009

The conventional paper retrieval is the keyword-based search and as a huge amount of data be published, this search becomes more difficult in retrieving information that user want to find. In order to search for information to the user's intent, we need to introduce semantic Web that represents semantics of Web document resources on the Internet environment as ontology and enables the computer to understand this ontology. Therefore, we describe a paper retrieval system through OWL(Ontology Web Language) ontology-based reason in this paper. We build the paper ontology based on OWL which is new popular ontology language for semantic Web and represent the correlation among diverse paper properties as the DL(description logic) query, and then this system infers the correct results from the paper ontology by using the DL query and makes it possible to retrieve information intelligently. Finally, we compared our experimental result with the conventional retrieval.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.774-779
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• 2007

최근 온라인 경매나 오픈 마켓 같은 온라인 전자상거래가 활발히 이루어지고 있다. 더불어 사용자가 PDA와 같은 단말기를 휴대하고 이동하는 동안 전자상거래가 이루어질 가능성이 높아지고 있다. 이러한 상황에서 온라인 전자상거래의 구매자와 판매자를 대신해서 협상을 수행하고 매매를 성사시키는 에이전트에 대한 연구가 시도되고 있다. 이를 확장하여 지능형 에이전트를 휴대형단말기에 적용함으로써, 모바일 환경에서 구매자와 판매자간의 전자상거래를 대행하는 협상 에이전트의 필요성이 부각되고 있다. 본 연구에서는 모바일 전자상거래환경에서 에이전트가 협상에 대한 합리적인 판단할 수 있도록 게임이론을 사용하여 모델화 하였고, 휴대형단말기가 블루투스를 통해 인근에 있는 상점을 탐색 및 블루투스 네트워크를 구성하도록 하였다. 또한, 사용자가 협상 항목을 단계적으로 변경할 수 있는 전략을 사용할 수 있게 하였으며, 이를 평가함수를 사용하여 협상해서 최종 거래 결정은 자동 또는 수동으로 성사되게 하였다. 기존 협상 모델은 가격과 배송 방법 같은 협상 항목에 대해 가중치만을 변경하여 만족도를 판단함으로써, 실질적인 항목의 변화는 없고 초기에 설정된 협상 항목이 변경되지 않는 문제점이 있었다. 본 연구에서는 다단계 전략을 사용하여 단계마다 사용자의 요구 사항을 변경시킬 수 있기 때문에, 초기에 설정한 협상 항목의 값이 단계별로 변경될 수 있어 사용자의 의도가 협상에 실질적으로 반영되는 효과가 있다. 더불어 오프라인 전자상거래에서는 구매자가 직접 상점을 방문하여 상품을 검색하고 협상하였다. 그러나, 본 연구에서는 이동중인 사용자의 인근에 위치한 상점 에이전트로부터 상품 정보를 받는다. 그 후에 에이전트가 구매 협상을 하기 때문에 사용자가 이동 중에 상가에 직접 들어가지 않고도 상품을 검색 및 협상 할 수 있는 장점이 있다. 본 논문에서는 제안한 모바일 쇼핑 에이전트를 구현하고, 협상 과정과 결과를 비교하여 모델의 타당성과 성능을 평가한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.3
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• pp.358-364
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• 2006

At present age, great many informations are no exaggeration to say that supply information of better quality to users depend on that grasp correctly user's query intention through internet along with fast development of internet. Therefore, this thesis suggest that generating meaning relation between keywords with that result by passing through morpheme analysis and syntactic analysis about Natural Language Query. This approach is implied more meaning relation than query by simple keyword or simple combination between keywords. Therefore, it is going to permit much more efficient information retrieval because of solving problem about existent query form, and generating query that user's query intention is reflected more correctly.

• The KIPS Transactions:PartB
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• v.11B no.3
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• pp.369-380
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• 2004

In this paper, we propose a web page weighting scheme based on WordNet-based collaborative evaluation and hyperlink to improve the precision of web search engine. Generally search engines use keyword matching to decide web page ranking. In the information retrieval from huge data such as the Web, simple word comparison cannot distinguish important documents because there exist too many documents with similar relevancy. In this paper, we implement a WordNet-based user interface that helps to distinguish different senses of query word, and constructed a search engine in which the implicit evaluations by multiple users are reflected in ranking by accumulating the number of clicks. In accumulating click counts, they are stored separately according to lenses, so that more accurate search is possible. Weighting of each web page by using collaborative evaluation and hyperlink is reflected in ranking. The experimental results with several keywords show that the precision of proposed system is improved compared to conventional search engines.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.816-822
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• 2016

Content-Based image retrieval is a method to search by image features such as local color, texture, and other image content information, which is different from conventional tag or labeled text-based searching. In real life data, the number of images having tags or labels is relatively small, so it is hard to search the relevant images with text-based approach. Existing image search method only based on image feature similarity has limited performance and does not ensure that the results are what the user expected. In this study, we propose and validate a machine learning based approach to improve the performance of the image search engine. We note that when users search relevant images with a query image, they would expect the retrieved images belong to the same category as that of the query. Image classification method is combined with the traditional image feature similarity method. The proposed method is extensively validated on a public PASCAL VOC dataset consisting of 11,530 images from 20 categories.