• Smart Media Journal
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• v.2 no.3
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• pp.17-22
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• 2013

The growth of the propagated NFC provides the various services with respect to internet applications, which it can be predicted from the simple internet services to the privated services. This paper proposes the clustering of information retrieval system model using NFC tag of access information for utilizing the similar information of the tag. The proposed model can search the similar information of the tag using the access information of NFC tag. In addition, it can cluster the similar retrieval information into topic cluster for utilizaing users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1444-1450
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• 2004

MPEG-7 based on XML represents various information of multimedia data's contents. and it support search and browsing by user's wants. But, MPEG-7 standard don't support retrieval method and Many XML Indexing is not compatible to retrieval MPEG-7 documents. So Much research activity and interest has emerged recently in retrieval MPEG-7 documents. In our paper, we suppose a hierarchical index based on MPEG-7 document's structural information, and review how to query processing based on high level feature description.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.491-503
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• 2002

In this paper, we propose a automatic document summarization method based on Principal Component Analysis(PCA) which is one of the multivariate statistical methods. After extracting thematic words using PCA, we select the statements containing the respective extracted thematic words, and make the document summary with them. Experimental results using newspaper articles show that the proposed method is superior to the method using either word frequency or information retrieval thesaurus.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.330-335
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• 2002

The most critical issue in information retrieval system is to have adequate results corresponding to user requests. When all documents related with user inquiry retrieve, it is not easy not only to find correct document what user wants but is limited. Therefore, clustering method that grouped by corresponding documents has widely used so far. In this paper, we cluster on the basis of the meaning rather than the index term in the existing document and a LSI method is applied by this reason. Furthermore, we distinguish and analyze differences from the clustering using widely-used K-Means algorithm for the document clustering.

• The Journal of Information Systems
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• v.14 no.3
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• pp.82-88
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• 2005

Much information has been hierarchically organized to facilitate information browsing, retrieval, and dissemination. In practice, much information may be entered at any time, but only a small subset of the information may be classified into some categories in a hierarchy. Therefore, achieving document filtering (DF) in the course of document classification (DC) is an essential basis to develop an information center, which classifies suitable documents into suitable categories, reducing information overload while facilitating information sharing. In this paper, we present a technique ICenter, which conducts DF and DC by recognizing the context of discussion (COD) of each document and category. Experiments on real-world data show that, through COD recognition, the performance of ICenter is significantly better. The results are of theoretical and practical significance. ICenter may server as an essential basis to develop an information center for a user community, which shares and organizes a hierarchy of textual information.

• Journal of Information Management
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• v.42 no.4
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• pp.137-154
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• 2011

A headword finding system is defined as an information retrieval system using a word gloss as a query. We use the gloss as a document in order to implement such a system. Generally the gloss is very short in length and then makes very difficult to find the most proper headword for a given query. To alleviate this problem, we expand the document using the concept of query expansion in information retrieval. In this paper, we use 2 document expansion methods : gloss expansion and similar word expansion. The former is the process of inserting glosses of words, which include in the document, into a seed document. The latter is also the process of inserting similar words into a seed document. We use a featureless clustering algorithm for getting the similar words. The performance (r-inclusion rate) amounts to almost 100% when the queries are word glosses and r is 16, and to 66.9% when the queries are written in person by users. Through several experiments, we have observed that the document expansions are very useful for the headword finding system. In the future, new measures including the r-inclusion rate of our proposed measure are required for performance evaluation of headword finding systems and new evaluation sets are also needed for objective assessment.

• Journal of the Korean Society for information Management
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• v.12 no.2
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• pp.213-223
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• 1995

It has known that different representations of either queries or documents, or different retrieval techniques retrieve different sets of documents. Recent works suggest that significant improvements in retrieval performance can be achieved by combining multiple representations or multiple retrieval techniques. In this paper we propose a simple method for retrieving different documents within a single query representation, a single document representation and a single retrieval technique. We classify the types of documents, and describe the properties of weighting schemes. Then. we explain that different properties of weighting schemes may retrieve different types of documents. Experimental results show that significant improvements can be obtained by combining the retrieval results form different properties of weighting schemes.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.451-460
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• 2001

In this paper, we propose an indexing model for efficient structure retrieval of XML documents. The proposed indexing model consists of structured information that supports a wide range of queries such as content-based queries and structure-attribute queries at all levels of the document hierarchy and index organizations that are constructed based on the information. To support structured retrieval, a new representation method for structured information is presented. Using this structured information, we design content index, structure index, and attribute index for efficient retrieval. also, we explain processing procedures for mixed queries and evaluate the performance of proposed indexing model. It is shown that the proposed indexing model achieves better retrieval performance than the existing method.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.421-431
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• 2023

Nuclear power plants (NPPs) have technical specifications (Tech Specs) to ensure that the equipment and key operating parameters necessary for the safe operation of the power plant are maintained within limiting conditions for operation (LCO) determined by a safety analysis. The LCO of Tech Specs that identify the lowest functional capability of equipment required for safe operation for a facility must be complied for the safe operation of NPP. There have been previous studies to aid in compliance with LCO relevant to rule-based expert systems; however, there is an obvious limit to expert systems for implementing the rules for many situations related to LCO. Therefore, in this study, we present a retrieval methodology for similar LCO cases in determining whether LCO is met or not met. To reflect the natural language processing of NPP features, a domain dictionary was built, and the optimal term frequency-inverse document frequency variant was selected. The retrieval performance was improved by adding a Boolean retrieval model based on terms related to the LCO in addition to the vector space model. The developed domain dictionary and retrieval methodology are expected to be exceedingly useful in determining whether LCO is met.

• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.243-248
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• 2012

In the information retrieval systems like vector model implementation and document clustering, document similarity calculation takes a great part on the overall performance of the system. In this paper, GPU parallelism has been explored to enhance the processing speed of document similarity calculation in a CUDA framework. The proposed method increased the similarity calculation speed almost 15 times better compared to the typical CPU-based framework. It is 5.2 and 3.4 times better than the methods by using CUBLAS and Thrust, respectively.