• Title/Summary/Keyword: 개념기반검색

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Automated Development of Rank-Based Concept Hierarchical Structures using Wikipedia Links (위키피디아 링크를 이용한 랭크 기반 개념 계층구조의 자동 구축)

  • Lee, Ga-hee;Kim, Han-joon
    • The Journal of Society for e-Business Studies
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    • v.20 no.4
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    • pp.61-76
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    • 2015
  • In general, we have utilized the hierarchical concept tree as a crucial data structure for indexing huge amount of textual data. This paper proposes a generality rank-based method that can automatically develop hierarchical concept structures with the Wikipedia data. The goal of the method is to regard each of Wikipedia articles as a concept and to generate hierarchical relationships among concepts. In order to estimate the generality of concepts, we have devised a special ranking function that mainly uses the number of hyperlinks among Wikipedia articles. The ranking function is effectively used for computing the probabilistic subsumption among concepts, which allows to generate relatively more stable hierarchical structures. Eventually, a set of concept pairs with hierarchical relationship is visualized as a DAG (directed acyclic graph). Through the empirical analysis using the concept hierarchy of Open Directory Project, we proved that the proposed method outperforms a representative baseline method and it can automatically extract concept hierarchies with high accuracy.

Estimation of Document Similarity using Semantic Kernel Derived from Helmholtz Machines (헬름홀츠머신 학습 기반의 의미 커널을 이용한 문서 유사도 측정)

  • 장정호;김유섭;장병탁
    • Proceedings of the Korean Information Science Society Conference
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    • 2003.04c
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    • pp.440-442
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    • 2003
  • 문서 집합 내의 개념 또는 의미 관계의 자동 분석은 보다 효율적인 정보 획득과 단어수준 이상의 개념 수준에서의 운서 비교를 가능하게 한다. 본 논문에서는 은닉변수모델을 이용하여 문서 집합으로부터 단어들 간의 의미관계를 자동적으로 추출하고 이를 통해 문서간 유사도 측정을 효과적으로 하기 위한 방안을 제시한다. 은닉변수 모델로는 다중요인모델의 학습이 용이한 헬름홀츠 머신을 활용하묘 이의 학습 결과에 기반하여, 문서간 비교를 한 의미 커널(semantic kernel)을 구축한다. 2개의 문서 집합 HEDLINE과 CACM 데이터에 대한 검색 실험에서, 제안된 기법을 적응함으로써 기본 VSM(Vector Space Model) 에 비해 20% 이상의 평균 정확도 향상을 이를 수 있었다.

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Design of State_based Planner with Intelligence and Reactivity in Real_Time Environment (실시간 환경에서 지능성과 반응성을 갖는 상황 기반 계획기 설계)

  • 박인숙;이태경
    • Proceedings of the Korea Multimedia Society Conference
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    • 1998.10a
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    • pp.365-370
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    • 1998
  • 정보 통신의 모든 분야에 걸쳐 활용될 수 있는 차세대 핵심 기술인 에이젼트는 자율성, 지능성, 반응성, 협동성을 갖는 독립된 프로그램으로 지식과 추론 능력을 바탕으로 사용자의 작업을 대신 해준다. 본 논문은 복잡하고 실시간 환경에서 발생할 수 있는 상황에 있어 지능적인 추론과 즉각적인 반응이 가능한 혼합형 에이전트 개념을 도입한 계획기를 설계한다. 계획기구성을 위하여, 재난 발생시 즉각적인 반응을 하는 반응요소(reflexive component)와 계획라이브러리에 저장된 여러 계획들을 저장된 계획들을 검색해 해결안을 찾는 인지요소(cognitive component)로 구성된다. 인지 요소에서 상황에 따라 저장된 계획을 찾고, 상황에 맞는 것을 추론하는 과정을 살펴본다. 혼합형 에이전트 개념을 도입한 계획기는 부분 순서화된 계획기로서 상황 기반탐색(situation-based search)방법에 의하여 계획을 생성하도록 하였다.

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Access Procedure of the SHADE based Shared Data for Supporting the Efficient Decision Making (효율적 의사결정 지원을 위한 SHADE 기반 공유 데이터 접근 절차)

  • Lee, Kyung-Hwan;Na, Yun-Geun;Yoon, Hee-Byung;Jo, Byoung-In
    • 한국IT서비스학회:학술대회논문집
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    • 2008.11a
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    • pp.204-207
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    • 2008
  • 본 논문에서는 효율적인 의사결정 지원을 위해 SHADE 기반의 공유 데이터 접근 활동들에 대한 절차를 제안한다. 먼저 SHADE에 대한 개념 및 기술구조를 제시하고 공유 데이터 접근을 위해 요구되는 핵심 기술, 즉 데이터 디렉토리 서비스 기술, 데이터 미디에이션, 복제 기술에 대한 개념과 특징을 분석한다. 그런 다음 SHADE 기술구조 하에 효율적으로 공유 데이터에 접근할 수 있도록 4개 활동 각각에 대해 절차를 제안한다. 제안한 절차에는 5단계의 디렉토리 서비스 및 4단계의 검색 절차, 데이터 미디에이션을 이용한 5단계의 데이터 중개 절차, 미들웨어를 이용한 7단계의 실시간 데이터 교환 및 4단계의 데이터 복제절차가 각각 포함된다. 향후 제안한 공유 데이터 접근 절차를 통해 정보체계 간 데이터 연결 능력이 향상될 뿐만 아니라 이를 통해 정확하고, 신속한 의사결정 지원에 도움을 줄 것으로 기대한다.

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A Design and Implementation of Intelligent Image Retrieval System using Hybrid Image Metadata (혼합형 이미지 메타데이타를 이용한 지능적 이미지 검색 시스템 설계 및 구현)

  • 홍성용;나연묵
    • Journal of Korea Multimedia Society
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    • v.3 no.3
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    • pp.209-223
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    • 2000
  • As the importance and utilization of multimedia data increases, it becomes necessary to represent and manage multimedia data within database systems. In this paper, we designed and implemented an image retrieval system which support efficient management and intelligent retrieval of image data using concept hierarchy and data mining techniques. We stored the image information intelligently in databases using concept hierarchy. To support intelligent retrievals and efficient web services, our system automatically extracts and stores the user information, the user's query information, and the feature data of images. The proposed system integrates user metadata and image metadata to support various retrieval methods on image data.

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A Semantic Web Service for Tourism Information over the Mobile Web (시맨틱 웹에 기초한 모바일 관광정보 서비스)

  • Lee, Yang-Won
    • Journal of the Korean Geographical Society
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    • v.42 no.5
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    • pp.788-807
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    • 2007
  • To better publish geographical information on the Web, it is important to capture how Web technologies are changing. For a recent decade, Semantic Web has been developed by incorporating ontologies into the current Web, with an aim to make computers understand rather than simply display. Ontology, an explicit specification of a conceptualization, and the Semantic Web grounded on the ontology, have the potential for effective sharing and appropriate retrieval of geographical information. This paper describes a Semantic Web Service over the mobile Web that can offer pertinent tourism information according to user contexts. To do this, a tourism ontology was formalized in the PARA(Place-Attraction-Resource-Activity) ontology model by organizing tourist places, tourist attractions, tourism resources, and activities. Locational relationships between tourist places were also included in the PARA ontology model to take into account the movements of tourists on a railway network. The XML(Extensible Markup Language) Web Service in the middle tier manages the client-side request for information retrieval and the corresponding server-side response from the data provider. The PARA ontology was integrated into the XML Web Service for the concept-based discovery of tourism information. The applicability of the proposed system was tested through a simulation experiment for Tokyo tourism.

Region Based Image Similarity Search using Multi-point Relevance Feedback (다중점 적합성 피드백방법을 이용한 영역기반 이미지 유사성 검색)

  • Kim, Deok-Hwan;Lee, Ju-Hong;Song, Jae-Won
    • The KIPS Transactions:PartD
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    • v.13D no.7 s.110
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    • pp.857-866
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    • 2006
  • Performance of an image retrieval system is usually very low because of the semantic gap between the low level feature and the high level concept in a query image. Semantically relevant images may exhibit very different visual characteristics, and may be scattered in several clusters. In this paper, we propose a content based image rertrieval approach which combines region based image retrieval and a new relevance feedback method using adaptive clustering together. Our main goal is finding semantically related clusters to narrow down the semantic gap. Our method consists of region based clustering processes and cluster-merging process. All segmented regions of relevant images are organized into semantically related hierarchical clusters, and clusters are merged by finding the number of the latent clusters. This method, in the cluster-merging process, applies r: using v principal components instead of classical Hotelling's $T_v^2$ [1] to find the unknown number of clusters and resolve the singularity problem in high dimensions and demonstrate that there is little difference between the performance of $T^2$ and that of $T_v^2$. Experiments have demonstrated that the proposed approach is effective in improving the performance of an image retrieval system.

A Concept-Based Approach for Abstracting Protein Interaction Networks (단백질 상호작용 네트워크을 위한 개념 기반 추상화)

  • Choi Jae-Hun;Park Jong-Min;Kim Ki-Heon;Park Seon-Hee
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.232-234
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    • 2005
  • 본 논문은 세포 내에 존재하는 방대한 단백질들 사이의 상호작용 관계 네트워크에서 생물학적인 의미 연관성을 가지는 부분 네트워크를 콤포지트로 추상화할 수 있는 방법을 제안한다. 이 추상화를 위해 네트워크에서 구조적으로 완전한 부분 네트워크, 개념적으로 인접한 부분 네트워크 그리고 두 조건을 모두 만족하는 부분네트워크를 탐색한다. 따라서, 사용자는 방대한 네트워크을 개념적인 관점에서 분석할 수 있으며, 특정한 의미을 가지는 부분 네트워크를 쉽게 검색할 수 있다.

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A Method for Extracting Relationships Between Terms Using Pattern-Based Technique (패턴 기반 기법을 사용한 용어 간 관계 추출 방법)

  • Kim, Young Tae;Kim, Chi Su
    • KIPS Transactions on Software and Data Engineering
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    • v.7 no.8
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    • pp.281-286
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    • 2018
  • With recent increase in complexity and variety of information and massively available information, interest in and necessity of ontology has been on the rise as a method of extracting a meaningful search result from massive data. Although there have been proposed many methods of extracting the ontology from a given text of a natural language, the extraction based on most of the current methods is not consistent with the structure of the ontology. In this paper, we propose a method of automatically creating ontology by distinguishing a term needed for establishing the ontology from a text given in a specific domain and extracting various relationships between the terms based on the pattern-based method. To extract the relationship between the terms, there is proposed a method of reducing the size of a searching space by taking a matching set of patterns into account and connecting a join-set concept and a pattern array. The result is that this method reduces the size of the search space by 50-95% without removing any useful patterns from the search space.

Personalized Bookmark Recommendation System Using Tag Network (태그 네트워크를 이용한 개인화 북마크 추천시스템)

  • Eom, Tae-Young;Kim, Woo-Ju;Park, Sang-Un
    • The Journal of Society for e-Business Studies
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    • v.15 no.4
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    • pp.181-195
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    • 2010
  • The participation and share between personal users are the driving force of Web 2.0, and easily found in blog, social network, collective intelligence, social bookmarking and tagging. Among those applications, the social bookmarking lets Internet users to store bookmarks online and share them, and provides various services based on shared bookmarks which people think important.Delicious.com is the representative site of social bookmarking services, and provides a bookmark search service by using tags which users attach to the bookmarks. Our paper suggests a method re-ranking the ranks from Delicious.com based on user tags in order to provide personalized bookmark recommendations. Moreover, a method to consider bookmarks which have tags not directly related to the user query keywords is suggested by using tag network based on Jaccard similarity coefficient. The performance of suggested system is verified with experiments that compare the ranks by Delicious.com with new ranks of our system.