• KSII Transactions on Internet and Information Systems (TIIS)
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• 제2권3호
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• pp.150-170
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• 2008

In recent years, main focus of research on image retrieval techniques is on content-based image retrieval. Text-based image retrieval schemes, on the other hand, provide semantic support and efficient retrieval of matching images. In this paper, based on Formal Concept Analysis (FCA), we propose a new image indexing and retrieval technique. The proposed scheme uses keywords and textual annotations and provides semantic support with fast retrieval of images. Retrieval efficiency in this scheme is independent of the number of images in the database and depends only on the number of attributes. This scheme provides dynamic support for addition of new images in the database and can be adopted to find images with any number of matching attributes.

• 한국컴퓨터정보학회논문지
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• 제10권5호
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• pp.17-26
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• 2005

최근 각종 정보가 증가함에 따라 효율적인 관리를 위해 정보 검색에 관한 연구가 더욱 활기를 띠고 있다. 현재 웹 환경에서 운영되고 있는 국내 유물 검색시스템의 경우 대부분이 키워드 기반의 텍스트 검색 방식을 채택하고 있다. 이러한 텍스트 검색 방식은 그 유물에 대한 정확한 이름이나 키워드를 질의자 (user)가 미리 알고 있어야 한다. 하지만 검색대상에 관한 정보가 부족하여 키워드가 모호하거나 단순히 형상에 관한 기억만 있을 경우에는 검색이 쉽지 않았다. 이 논문에서는 기존 유물 검색 시스템의 문제점을 해결하기 위해 온톨로지 기반의 택스트 질의와 사용자 스케치 이미지 질의를 사용하는 자바 기반의 혼합형 유물 검색시스템을 제안한다. 이 시스템은 국내 유물들을 대상으로 사용자가 기억하고 있는 유물에 관한 정보의 형태(택스트, 형상 등)에 따라 다양한 질의방법을 제공하며, 검색결과 내에서 온톨로지 의미관계를 이용한 추가검색이 가능하다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권1호
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• pp.26-32
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• 2002

The objectives of this paper are twofold. First is to introduce a model for representing documents with semantics relatedness using rough sets but with tolerance relations instead of equivalence relations (TRSM). Second is to introduce two document hierarchical and nonhierarchical clustering algorithms based on this model and TRSM cluster-based information retrieval using these two algorithms. The experimental results show that TRSM offers an alterative approach to text clustering and information retrieval.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권3호
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• pp.522-538
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• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.240-245
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• 1998

Fuzzy information retrieval which uses the concept of fuzzy relation is able to retrieve documents in the way based on not morphology but semantics, dissimilar to traditional information retrieval theories. Fuzzy information retrieval logically consists of three sets : the set of documents, the set of terms and the set of queries. It maintains a fuzzy relational matrix which describes the relationship between documents and terms and creates a thesaurus with fuzzy relational product. It also provides the user with documents which are relevant to his query. However, there are some problems on building a thesaurus with fuzzy relational product such that it has big time complexity and it uses fuzzy values to be processed with flating-point. Actually, fuzzy values have to be expressed and processed with floating-point. However, floating-point operations have complex logics and make the system be slow. If it is possible to exchange fuzzy values with binary values, we could expect sp eding up building the thesaurus. In addition, binary value expressions require just a bit of memory space, but floating -point expression needs couple of bytes. In this study, we suggest a new method of building a thesaurus, which accelerates the operation of the system by pre-applying an ${\alpha}$-cut. The experiments show the improvement of performance and reliability of the system.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.648-651
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• 2013

The information generated in large-scale and complex construction projects are transferred continuously and transformed into project products on the long span life cycle. Therefore, information flow management is related with the success of project directly. However, certain characteristics of large-scale and complex construction projects make the solving the problem more difficultly. Although several information retrieval systems support the information management system, it is not suitable to grasp information flows. Hence, we developed an information retrieval system specialized with the information flow based on a preceding research. The system consists of a relation-based database and the process information transferring relation inference application module. The system enables project managers to manage the entire project process more efficiently and each project member to work their own task being served the information flow retrieval results.

• 정보관리학회지
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• 제16권4호
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• pp.125-150
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• 1999

본 연구는 정보검색시스템에서 중요한 역할을 하는 이용자 인터페이스의 효용성을 높이기 위해서 시도된 다양한 기술 및 기법을 다각적으로 조사하였다. 특히 질의어처리 인터페이스, 탐색전략 인터페이스, 적합성 피드백 인터페이스를 중점으로 탐색관련 인터페이스 기능과 문헌 브라우즈 인터페이스, 탐색결과 브라우즈 인터페이스와 같은 브라우즈 관련 인터페이스 기능에 대하여 중점적으로 살펴보았다. 앞으로의 이용자 인터페이스 기능은 시각적 검색 기법, 인공지능 기법, 멀티모드 커뮤니케이션 기법 등이 많이 사용될 것으로 보았다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5197-5218
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• 2019

Large-scale retrieval algorithm is problem for visual analyses applications, along its research track. In this paper, we propose a high-efficiency region division-based image retrieve approaches, which fuse low-level local color histogram feature and texture feature. A novel image region division is proposed to roughly mimic the location distribution of image color and deal with the color histogram failing to describe spatial information. Furthermore, for optimizing our region division retrieval method, an image descriptor combining local color histogram and Gabor texture features with reduced feature dimensions are developed. Moreover, we propose an extended Canberra distance method for images similarity measure to increase the fault-tolerant ability of the whole large-scale image retrieval. Extensive experimental results on several benchmark image retrieval databases validate the superiority of the proposed approaches over many recently proposed color-histogram-based and texture-feature-based algorithms.

• International Journal of Contents
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• 제1권2호
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• pp.39-43
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• 2005

In this paper, we describe a generation mechanism of semantic-based queries for high accuracy information retrieval and question answering. It is difficult to offer the correct retrieval result because general information retrieval systems do not analyze the semantic of user's natural language question. We analyze user's question semantically and extract semantic features, and we .generate semantic-based queries using them. These queries are generated using the se-mantic-based question analysis grammar and the query generation rule. They are represented as semantic features and grammatical morphemes that consider semantic and syntactic structure of user's questions. We evaluated our mechanism using 100 questions whose answer type is a person in the TREC-9 corpus and Web. There was a 0.28 improvement in the precision at 10 documents when semantic-based queries were used for information retrieval.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2002년도 춘계학술대회 논문집
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• pp.3-8
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• 2002

This paper introduces the basic concept of computational modeling of perception processes for multimedia data. Such processes are modeled as hierarchical inter- and intra- relationships amongst information in physical, physiological, psychological and cognitive layers in perception. Based on our framework, this paper gives the algorithms for content-based retrieval for multimedia database systems.