• Journal of information and communication convergence engineering
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• v.1 no.3
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• pp.143-146
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• 2003

In the study, a new-concept search agent system for the WWW by using XML-based technology is proposed. The implementation of the prototype of this proposed system, the comparison with traditional search engines, and the evaluation of the prototype system are also.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2003.05a
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• pp.101-106
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• 2003

This paper introduces the basic concept of computational modeling of perception processes for multimedia data. Such processes are modeled as hierarchical inter-and 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.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.434-445
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• 2009

Content-based image retrieval(CBIR) is the retrieval technique which uses the contents of images. However, in contrast to text data, multimedia data are ambiguous and there is a big difference between system's low-level representation and human's high-level concept. So it doesn't always mean that near points in the vector space are similar to user. We call this the semantic-gap problem. Due to this problem, performance of image retrieval is not good. To solve this problem, the relevance feedback(RF) which uses user's feedback information is used. But existing RF doesn't consider user's region-of-interest(ROI), and therefore, irrelevant regions are used in computing new query points. Because the system doesn't know user's ROI, RF is proceeded in the image-level. We propose a new ROI RF method which guides a user to select ROI from relevant images for the retrieval of complex satellite image, and this improves the accuracy of the image retrieval by computing more accurate query points in this paper. Also we propose a pruning technique which improves the accuracy of the image retrieval by using images not selected by the user in this paper. Experiments show the efficiency of the proposed ROI RF and the pruning technique.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.766-771
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• 2006

In this paper, we focus on the building domain ontology from corpus by extracting concepts and properties relationships based on linguistic patterns. The pharmacy field is selected as an experiment domain and we present an algorithm to extract hierarchical structure for terminology based on the noun/suffix patterns of terminology in domain texts. In order to show usefulness of our domain ontology, we compare a typical keyword based retrieval method with an ontology based retrieval mettled which uses related information in an ontology for a related feedback. As a result, our method shows the improvement of precision by 4.97% without losing recall.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1093-1102
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• 1996

For the reuse, configuration management, and version control of softwares, the composition of retrieval systems and library are most important matters, which makes it possible to retrieve the concerned software components. Retrieval systems, which is able to store many components, must make it possible to retrieve the concerned components with deadwoods in the fastest way. Based either on keyboards or the concept of inverted file on the part of content is usually used in the current retrieval systems. However, in this paper, new retrieval systems are suggested with using set and bag class with Smalltalk language, one of object- oriented programming language, based either on the keywords or on the part of content to find out the concerned components. This method is improved the function of user interface and its management, In this paper, library is also suggested along with the new retrieval systems, and user interface is designed and implemented for its management and control. The new retrial systems of this paper can be employed by interface in another language, and this system is to provide the concerned user with the appropriate retrieval systems and library for the version control.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.351-357
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• 2013

Information retrieval by query keywords have some mismatching problems to fit user's requirement for the retrieved documents due to the varieties of users. These problems are originated from the different situations and characteristics of user's requirement. Also, it has a problem that general correlation coefficients did not display the information relations. In this thesis, it is to suggest knowledge retrieval system to verify feasibility of personnel selection procedure and results supporting selection rules after construction of personnel selection ontologies and rules composed of various concept and knowledge based on the semantic web technology. In the suggested system, it is to clear disadvantages of limited information retrieval providing the suitable information to satisfy user's different situations and characteristics using Spearman's coefficients. Experimental results by this semantic-based information retrieval show 90.3% of accuracy and 71.8% of recall compared with legacy keyword information retrieval.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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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.

• The Journal of the Korea Contents Association
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• v.6 no.3
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• pp.20-27
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• 2006

In this paper we constructed semantic net that can efficiently conform retrieval and reuse of object-oriented source code. In order that initial relevance of semantic net was constructed using thesaurus to represent concept of object-oriented inheritance between each node. Also we made up for the weak points in spreading activation method that use to activate node and line of semantic net and to impulse activation value. Therefore we proposed the method to enhance retrieval time and to keep the quality of spreading activation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.134-137
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• 2003

Both browsing and retrieval with search engines are major operations that establish the interaction between users and the Web. Although both operations are usually combined to locate information from the Web, recent growth of the Web has overtaken the potential of this conventional interaction. This paper proposes the concept of Retrieve, Browse, and Analyze (RBA)-based interactions, as the improvement of the conventional Retrieve and Browse (RB)-based interaction. The prototype interface based on RBA-based interaction is also presented.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.389-397
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• 2017

Recently semantic web document is produced and added in repository in a cloud computing environment and requires an intelligent semantic agent for analytical classification of documents and information retrieval. The traditional methods of information retrieval uses keyword for query and delivers a document list returned by the search. Users carry a heavy workload for examination of contents because a former method of the information retrieval don't provide a lot of semantic similarity information. To solve these problems, we suggest a key word frequency and concept matching based semantic clustering model using hadoop and NoSQL to improve classification accuracy of the similarity. Implementation of our suggested technique in a cloud computing environment offers the ability to classify and discover similar document with improved accuracy of the classification. This suggested model is expected to be use in the semantic web retrieval system construction that can make it more flexible in retrieving proper document.