• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.51-55
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• 2001

With the rapid growth of the World Wide Web and electronic information services, information is becoming available on-Line at an incredible rate. One result is the oft-decried information overload. No one has time to read everything, yet we often have to make critical decisions based on what we are able to assimilate. The technology of automatic text summarization is becoming indispensable for dealing with this problem. Text summarization is the process of distilling the most important information from a source to produce an abridged version for a particular user or task. Information retrieval(IR) is the task of searching a set of documents for some query-relevant documents. On the other hand, text summarization is considered to be the task of searching a document, a set of sentences, for some topic-relevant sentences. In this paper, we show that document information, that is more reliable and suitable for query, using document length normalization of which is gained through information retrieval . Experimental results of this system in newspaper articles show that document length normalization method superior to other methods use query itself.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.3
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• pp.192-195
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• 2008

People have tendency of forgetting music title, though they easily remember particular part of music. If a music search system can find the title through a part of melody, this will provide very convenient interface to users. In this paper, we propose an algorithm that enables this type of search using feature transformation function. The original music is transformed to new feature information with sequential melodies. When a melody that is a part of search music is given to the system, the music retrieval system searches the music similar to the feature information of the melody. Moreover, this transformation function can be easily extended to various music recognition systems.

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.17-32
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• 1995

본 논문에서는 추론엔진 (inference engine)내에 퍼지정보 검색부(Fuzzy Information Retrieval part)를 갖는 교통신도 제어 전문가 시스템을 제안한다. 제안하는시스템은 다양하고 복잡한 도로 상화을 고려하여 그에 따른 적절한 주기를 각 도로별로 할당함으로써 원활한 교통 흐름을 제어한다. 추론엔진내의 퍼지정보 검색부는 퍼지 삼각 논리곱을 이용하여 도로의 상황을 분석한 후 각 도로에 맞는 가장 적절한 신호주기를 생성한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.745-751
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• 2004

In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM(Max and Min Model), Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly In this paper we propose a new soft evaluation method for web Information retrieval using local context analysis feedback model. We also show through performance comparison that local contort analysis feedback is more efficient and effective than MMM, Paice and P-norm.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.252-257
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• 2001

In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM, Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly. In this paper we propose a new soft evaluation method for Information retrieval using query splitting relevance feedback model. We also show through performance comparison that query splitting relevance feedback(QSRF) is more efficient and effective than MMM, Paice and P-norm.

• The Journal of Information Technology
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• v.4 no.2
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• pp.69-81
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• 2001

In this paper, we examine work in the evolution of content-based retrieval systems that rely on an intelligent infrastructure. Here, we refer to intelligence as the capabilities of the systems to build and maintain situational or world models, utilize dynamic knowledge representations, exploit context and overage advanced reasoning and learning capabilities. We argue that these elements are essential to producing effective systems for retrieving visual information at semantic levels matching those of human perception and cognition. In this paper, we review relevant research on the understanding of human intelligence and construction of intelligent systems in the fields of cognitive psychology, artificial intelligence, semiotics. We also discuss how some of the principal ideas from these fields lead to new opportunities and capabilities for content-based retrieval systems. Finally, we discribe some of our efforts in these directions. In particular, we present MediaNet, a multimedia knowledge presentation framework that facilitate and enable intelligent content-based retrieval.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.154-162
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• 2019

Despite the development of information and communication technology, which has a great impact on society and culture, there is no platform that provides a systematic classification and state-of-the-art information retrieval system on the traditional culture. Therefore, this paper developed a traditional culture retrieval system capable of convergence services with systematic classification and retrieval based on automatically generate and visualize the 3D timeline. This system provides the function of collecting traditional culture contents, classifying and storing collected traditional culture contents, and automatically generating 3D digital timeline based on stored traditional culture contents. In addition, a system satisfaction questionnaire was developed to evaluate the usability of the system, and 19 students participated in verifying the system. As a result of the experiment, the satisfaction of the system showed that all items were 'satisfied' on average.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.203-208
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• 2006

The management of image information settles as an important field with the advent of multimedia age and we are in need of the effective retrieval method to manage systematically image information. This paper has complemented the problem caused by the absence of space information that is a weak point of the existing color histogram method by assigning regions of features, and raised accuracy by adding texture and shape information. And existing methods using multiple features have problems that the retrieval process is embarrassed because each weight is set up manually. So we has solved these problems by assignment of weight applying fuzzy integral. As a result of experimenting with 1,000 color images, the proposed method showed better precision and recall than the existing method.

• Journal of Computing Science and Engineering
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• v.11 no.1
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• pp.24-31
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• 2017

Face-based video retrieval has become an active and important branch of intelligent video analysis. Face profiling and matching is a fundamental step and is crucial to the effectiveness of video retrieval. Although many algorithms have been developed for processing static face images, their effectiveness in face-based video retrieval is still unknown, simply because videos have different resolutions, faces vary in scale, and different lighting conditions and angles are used. In this paper, we combined content-based and semantic-based image analysis techniques, and systematically evaluated four mainstream local features to represent face images in the video retrieval task: Harris operators, SIFT and SURF descriptors, and eigenfaces. Results of ten independent runs of 10-fold cross-validation on datasets consisting of TED (Technology Entertainment Design) talk videos showed the effectiveness of our approach, where the SIFT descriptors achieved an average F-score of 0.725 in video retrieval and thus were the most effective, while the SURF descriptors were computed in 0.3 seconds per image on average and were the most efficient in most cases.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.814-826
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• 2005

The user-centric broadcasting environment includes the agent system and personalized broadcasting services for user-adaptive TV watching. In this paper, we propose broadcasting environment consisting of personalized broadcasting services and a multi-agent broadcasting system for the services. The proposed system employs the intelligent agent technology of the Foundation for Intelligent Physical Agents (FIPA) as well as metadata technology of MPEG-7 and TV-Anytime Forum (TVAF). To verify the usefulness of the proposed environment, we implemented a test-bed and demonstrated the proposed agent system with three services including intelligent user-information management service, information mobility service, and content retrieval service.