• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.22-28
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• 2008

This paper aims to offer a solution based on semantic document classification to improve e-Government utilization and efficiency for people using their own information retrieval system and linguistic expression. Generally, semantic document classification method is an approach that classifies documents based on the diverse relationships between keywords in a document without fully describing hierarchial concepts between keywords. Our approach considers the deep meanings within the context of the document and radically enhances the information retrieval performance. Concept Weight Document Classification(CoWDC) method, which goes beyond using existing keyword and simple thesaurus/ontology methods by fully considering the concept hierarchy of various concepts is proposed, experimented, and evaluated. With the recognition that in order to verify the superiority of the semantic retrieval technology through test results of the CoWDC and efficiently integrate it into the e-Government, creation of a thesaurus, management of the operating system, expansion of the knowledge base and improvements in search service and accuracy at the national level were needed.

• Journal of Korean Library and Information Science Society
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• v.40 no.3
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• pp.367-387
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• 2009

The similar bibliographic retrieval system follows whether it selects a thing of the extracted index term and or not the difference in which the similar document retrieval system There be many in the search result is generated. In this research, the method minimally making the error of the selection of the extracted candidate index term is provided In this research, the word information in which it is adjacent by using candidate index terms extracted from the similar literature and the keyword topic information were used. And by using the related author information and the reranking method of the search result, the similar bibliographic system in which an accuracy is high was developed. In this paper, we conducted experiments for similar bibliographic retrieval system on a collection of Korean journal articles of science and technology arena. The performance of similar bibliographic retrieval system was proved through an experiment and user evaluation.

• The Transactions of the Korea Information Processing Society
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• v.3 no.4
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• pp.720-732
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• 1996

Spatial match retrieval methods for iconic image databases recognize an image document as several icon symbols. Therefore the iconic symbols are used as primary keys to index the image document. When a user requires content-based retrieval ofimages, a spatial match retrieval method converts a query image into iconic symbols and then retrieves relevant images by accessing stored images. In order to support content-based image retrieval efficiently, we, in this paper, propose spatial match retrieval methods using signatures for iconic image databases. For this, we design new index representations of two-dimensional iconic images and explain implemented system.. In addition, we compare the conventional 9-DLT and our two-dimensional image retrieval method in terms of retrieval precision and recall ratio. We show that our method is more efficient than the conventional method.

• Journal of the Korean Society for information Management
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• v.7 no.1
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• pp.79-95
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• 1990

A retrieval technique was defined as a technique for comparing the document representations. So this study classified retrieval technique in terms of the charactristics of the retrieved set of documents and the representations that are used. The distinction is whether the set of retrieved documents contains only documents whose representations are an exact match with the query, or a partial match with query. For a partial match, the set of retrieved document will include also those that are an exact match with the query. Boolean-logic as one of the exact match retrieval techniques is in current in most of the large operational information retrieval systems despite of its problems and limitatlons. Partial match as an alternative technique has also various problems. Existing information retrieval systems are successful in aSSisting the user whose needs are well- defined (e.g. Boolean-logic), to retrieve relevant documents but it should be successful in providing retrieval assistance to the browser whose information requirements is ill-defined.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1786-1797
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• 2010

Automatic understanding of contents in document image is a very hard problem due to involvement with mathematically challenging problems originated mainly from the over-determined system induced by document segmentation process. In both academic and industrial areas, there have been incessant and various efforts to improve core parts of content retrieval technologies by the means of separating out segmentation related issues using semi-structured document, e.g., invoice,. In this paper we proposed classification models for text lines on invoice document in which text lines were clustered into the five categories in accordance with their contents: purchase order header, invoice header, summary header, surcharge header, purchase items. Our investigation was concentrated on the performance of machine learning based models in aspect of linear-discriminant-analysis (LDA) and non-LDA (logic based). In the group of LDA, na$\"{\i}$ve baysian, k-nearest neighbor, and SVM were used, in the group of non LDA, decision tree, random forest, and boost were used. We described the details of feature vector construction and the selection processes of the model and the parameter including training and validation. We also presented the experimental results of comparison on training/classification error levels for the models employed.

• The Journal of the Acoustical Society of Korea
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• v.26 no.3E
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• pp.74-79
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• 2007

In this paper, we report our recent work on a indexing and retrieval system of broadcast news using audio content analysis. Key issues addressed in this work are two major parts of the audio indexing system: anchorperson detection based on audio segmentation, and phone-based spoken document retrieval, developed in the framework of the emerging MPEG-7 standard. Experiments are conducted on a database of Britisch broadcast news videos. We discuss the development of the retrieval system, and the evaluation of each part and the retrieval system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.683-689
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• 2003

Information retrieval must be able to search the most suitable document that user need from document set. If foretell document adaptedness by similarity degree about QL(Query Language) of document, documents that search person does not require are searched. In this paper, showed that can search the most suitable document on user's request searching document of the whole space using genetic algorithm and used knowledge-base operator to solve various model's problem.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.222-226
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• 2003

Information retrieval must be able to search the most suitable document that user need from document set. If foretell document adaptedness by similarity degree about QL(Query Language) of document, documents that search person does not require are searched. In this paper, showed that can search the most suitable document on user's request searching document of the whole space using genetic algorithm and used knowledge-base operator to solve various model's problem.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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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.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.31-37
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• 2003

This paper is a review of the large-scale information retrieval system, CONDOR. This system was developed by the consortium that consists of Chonbuk National University, Searchline Co. and Carnegie Mellon University. This system is based on the probabilistic model of information retrieval systems. The multi-language query processing, online document summarization based on query and dynamic hierarchy clustering of this system make difference of other systems. We test this system with 30 million web documents successfully.