• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.566-568
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• 2009

사용자의 의도에 맞는 정보를 검색하기 위해서는 인터넷 환경에서 웹 문서 자원 사이의 의미 정보를 온톨로지로 표현하고, 이 온톨로지를 컴퓨터가 이해할 수 있게 하는 시맨틱 웹의 도입이 필요하다. 본 논문에서는 OWL 온톨로지 기반의 추론을 통한 논문 정보 검색시스템에 대하여 논한다. 시맨틱 웹의 새로운 온톨로지 언어로 부상한 OWL 기반의 논문 온톨로지를 구축하고, 논문 속성들 간의 다양한 상관관계를 서술논리 쿼리로 작성한다. 검색시스템은 이 쿼리를 기반으로 논문 온톨로지에 대하여 추론함으로써 지능적인 정보 검색이 가능하도록 하였다.

• Journal of the Korean Society for Library and Information Science
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• v.43 no.3
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• pp.163-180
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• 2009

In this paper, we describe a developmental system for establishing personal information tendency based on user queries. For each query, the system classified it based on the category information using a kNN classifier. As category information, we used DDC field which is already assigned to each record in the database. The system accumulates category information for all user queries and the user's personalized feature for the target database. We then developed a personalized retrieval system reflecting the personalized feature to produce search result. Our system re-ranks the result documents by adding more weights to the documents for which categories match with the user's personalized feature. By using user's tendency information, the ambiguity problem of the word could be solved. In this paper, we conducted experiments for personalized search and word sense disambiguation (WSD) on a collection of Korean journal articles of science and technology arena. Our experimental result and user's evaluation show that the performance of the personalized search system and WSD is proved to be useful for actual field services.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.12
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• pp.756-771
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• 2003

Digital Video Library System which manages a large amount of multimedia information requires efficient and effective retrieval methods. In this paper, we propose and implement a new video search and retrieval algorithm that compares the query video shot with the video shots in the archives in terms of foreground object, background image, audio, and its context. The foreground object is the region of the video image that has been changed in the successive frames of the shot, the background image is the remaining region of the video image, and the context is the relationship between the low-level features of the adjacent shots. Comparing these features is a result of reflecting the process of filming a moving picture, and it helps the user to submit a query focused on the desired features of the target video clips easily by adjusting their weights in the comparing process. Although the proposed search and retrieval algorithm could not totally reflect the high level semantics of the submitted query video, it tries to reflect the users' requirements as much as possible by considering the context of video clips and by adjusting its weight in the comparing process.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.487-492
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• 2008

Most Web search engines use ranking methods that take both the relevancy and the importance of documents into consideration. The importance of a document denotes the degree of usefulness of the document to general users. One of the most successful methods for estimating the importance of a document has been Page-Rank algorithm which uses the hyperlink structure of the Web for the estimation. In this paper, we propose a new importance estimation algorithm for the blog environment. The proposed method, first, calculates the importance of each document using user's bookmark and click count. Then, the Guru point of a blogger is computed as the sum of all importance points of documents which he/she wrote. Finally, the guru points are reflected in document ranking again. Our experiments show that the proposed method has higher correlation coefficient than the traditional methods with respect to correct answers.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.495-504
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• 2008

Recently, there has been much work on supporting keyword search not only for text documents, but a]so for structured data such as relational data, XML data, and RDF data. In this paper, we propose an efficient keyword search method for RDF data. The proposed method first groups related nodes and edges in RDF data graphs to reduce data sizes for efficient keyword search and to allow relevant information to be returned together in the query answers. The proposed method also utilizes the semantics in RDF data to measure the relevancy of nodes and edges with respect to keywords for search result ranking. The experimental results based on real RDF data show that the proposed method reduces RDF data about in half and is at most 5 times faster than the previous methods.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.102-104
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• 1998

본 시스템은 현재 연구 개발중인 정보에이전트 시스템의 일부로서 특정분야에 대한 사용자의 관심 주제에 관련된 정보와 함께 적절한 문서를 제공하는 지식 기반 시스템이다. 이러한 목적을 위해서 본 시스템의 지식베이스는 구조적인 방식으로 표현된 BKB(Biology Knowledge Base)와 DIC(DICtionary)로 구성된다. DIC는 특정분야에서 일반적으로 사람들이 사용하는 용어와 학명을 기준으로 하는 시스템에서 사용하는 용어와의 관계와 그러한 용어들간의 동의어 관계를 갖고 있다. 또한 BKB는 동물에 관련된 지식베이스로써 상위.하위 개념과 함께 사용자가 원하는 정보를 제공하기 위해 객체의 속성과 이에 관계된 값들을 포함한다. 본 시스템은 문서를 검색할 때 사용자 초기 질의를 상위.하위 개념 그리고 동의어로 확장할 뿐만 아니라 사용자 의도의 정확한 표현을 위해서 제공하는 다양한 질의 형식에 따른 질의 처리 결과로도 확장하므로 효과적인 문서 검색 결과를 보인다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.276-278
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• 2012

모바일 환경에서 정보 검색 시, 사용자가 질의를 구체적으로 입력하는 것이 번거로운 문제점이 있다. 본 논문은 모바일 환경에서의 효율적인 검색 성능 향상을 위해 단일 문서 피드백을 이용한 개념적인 재순위화 방법을 제안한다. 사용자는 질의 의도와 관련있는 문서 하나를 시스템에 피드백한다. 제안한 방법은 피드백된 문서와 앞서 검색된 문서들을 위키피디아의 표제어로 표현되는 개념적인 차원으로 맵핑함으로써 개념적인 수준에서 검색 결과를 재순위화한다. 최근 한국어 뉴스 및 블로그를 대상으로 한 실험 결과 키워드 기반 피드백 방법에 비해 제안한 방법이 높은 성능을 보였다.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.708-714
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• 2006

The World Wide Web has become an entrenched global medium for storing and searching information. Most people begin at a Web search engine to find information, but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is Web spamming as Google bombing that is based on the PageRank algorithm, one of the most famous Web structuring techniques. In this paper, we regard the Web as a directed labeled graph that Web pages represent nodes and the corresponding hyperlinks edges. In the present work, we define the label of an edge as having a link context and a similarity measure between link context and the target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. A motivating example is investigated in terms of the Singular Value Decomposition with which our algorithm can outperform to filter the Web spamming pages effectively.

• 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.