• Journal of the Korean BIBLIA Society for library and Information Science
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• v.15 no.1
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• pp.23-41
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• 2004

In indexing and organizing Web resources, there have been two basic methods: automatic indexing by extracting key words and library classification schemes or subject directories of search engines. But, both methods have failed to satisfy the user's information needs, due to the lack of standard criteria and the irrationality of its structural system. In this paper I have examined the limits of library classification scheme's structures and the problems related to the nature of Web resources such as specificity and exhaustivity. I have also attempted to explain the logicality of Web resources organization by facet analysis and its strengths and limitations. In so doing, I have proposed three specific methods in using facet analysis: firstly, indexing system by facet analysis; secondly, the alternative transformation of the enumerative classification scheme into facet classification scheme; and finally, the facet model of subject directory of domestic search engine. After examining the three methods, my study concludes that a controlled vocabulary by facet analysis can be employed as a useful method in organizing Web resources.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.10-19
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• 2002

In searching and locating a collection of components on the Web, users require a Web browser. Since the Web libraries tend to grow rapidly, there needs to be an effective way to organize and manage such large libraries. Traditional Web-based library(retrieval) systems provide various classification scheme and retrieval services to store and retrieve components. However, these systems do not include invaluable services, for example, enabling users to grasp the overall contents of the library at the beginning of retrieval. This paper discusses a Web-based library system, which provides the efficient management of object-oriented components and a set of services beyond simple component store and retrieval. These services consist of component comprehension through a reverse engineering process, automated summary extraction, and comprehension-based retrieval. Also, The performance of an automated cluster-based classification scheme adopted on the system is evaluated and compared with the cluster-based classification scheme adopted on the system is evaluated and compared with the performance of two other systems using traditional classification scheme.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.23-37
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• 1994

In this paper, we design and implement the prototype system, and propose the Extended Faceted Classification. Scheme and the Hybrid Retrieval Method that support classifying the software components, storing in library, and efficient retrieval according to user's request. In order to designs the classification scheme, we identify several necessary items by analyzing basic classes of software components that are to be classified. Then, we classify the items by their characteristics, decide the facets, and compose the component descriptors. According to their basic characteristics, we store software components in the library by clustering their application domains and are assign weights to the facets and its items to describe the component characteristics. In order to retrieve the software components, we use the retrieval-by-query model, and the weights and similarity for easy retrieval of similar software components. As the result of applying proposed classification scheme and retrieval model, we can easily identify similar components and the process of classification become simple. Also, the construction of queries becomes simple, the control of the size and order of the components to be retrieved possible, and the retrieval effectiveness is improved.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.6 no.1
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• pp.81-109
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• 1984

The purpose of this research is (i) to establish the principles particularly appropriate for the arrangement of archival collections is korea, and (ii) to produce a workable model of classification scheme in conformity with the established principles. The archival collections in korea are roughly devided into two groups as follows. (1) The collections of professional institutions of archives such as Korean National Archives. (2) The collections preserved by libraries, museums, and other similar institutions as a secondary collection, and these groups of collections are generally non-systematic collecting. For the arrangement of the former collections, the concept of "respect des fonds" which is universally accepted principies in archives are also applicable. But in case of the arrangement of the latter collections, the above mentioned principles are inappropriate because its collections a re built in separate pieces of documents and records without any relevance to the original function or structure of the corporation. Consequantly it is badly needed to make some devices for the arrangement of these archival collections since the archival collections of korea, in the majority of cases, belong to the latter. The author produced a tentative classification scheme, and adapted the korean traditional form (or type) of documents and records as a cardinal principle of the classification. The scheme is presented at the end of this paper.

• Korean Journal of Remote Sensing
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• v.19 no.4
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• pp.329-339
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• 2003

In this study, an approach of image fusion in decision level has been proposed for unsupervised image classification using the images acquired from multiple sensors with different characteristics. The proposed method applies separately for each sensor the unsupervised image classification scheme based on spatial region growing segmentation, which makes use of hierarchical clustering, and computes iteratively the maximum likelihood estimates of fuzzy class vectors for the segmented regions by EM(expected maximization) algorithm. The fuzzy class vector is considered as an indicator vector whose elements represent the probabilities that the region belongs to the classes existed. Then, it combines the classification results of each sensor using the fuzzy class vectors. This approach does not require such a high precision in spatial coregistration between the images of different sensors as the image fusion scheme of pixel level does. In this study, the proposed method has been applied to multispectral SPOT and AIRSAR data observed over north-eastern area of Jeollabuk-do, and the experimental results show that it provides more correct information for the classification than the scheme using an augmented vector technique, which is the most conventional approach of image fusion in pixel level.

• Journal of Korean Library and Information Science Society
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• v.30 no.3
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• pp.53-96
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• 1999

This study intends to : 1) confirm the possibility to transform the enumerated scheme into the faceted scheme, 2) review general theories on facet structure employed in DDC of the enumerated scheme, 3) analyze the facet structure of life science and literature in DDC, and 4) comparison of the facet structure of life science and literature in DDC and CC. This study suggests following conclusions. 1) CC follows throughly the classification principles by Ranganathan, but all classification theories are not property applied to DDC yet. 2) Because DDC does not have any formula to classify the compound subject, but has to follow the compounding methods presented in each subject, its facet structure is too complicated. 3) DDC has transformed the entire system into the facet structure through its revision. Expecially the life science transformed into the facet structure employed the facet indicators and applies them to all the systems in life science. But the notations have sometimes twofold meanings, and no ability to differentiate the meanings in the same notation,. When DDC follows the classification method by facet, the number of items for classification so limited that it is difficult to array the subdivision and that length of notation becomes longer and longer.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.8
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• pp.741-751
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• 2000

To achieve high performance by exploiting instruction level parallelism aggressively in superscalar processors, it is necessary to overcome the limitation imposed by control dependences and data dependences which prevent instructions from executing parallel. Value prediction is a technique that breaks data dependences by predicting the outcome of an instruction and executes speculatively its data dependent instruction based on the predicted outcome. In this paper, a hybrid value prediction scheme with dynamic classification mechanism is proposed. We design a hybrid predictor by combining the last predictor, a stride predictor and a two-level predictor. The choice of a predictor for each instruction is determined by a dynamic classification mechanism. This makes each predictor utilized more efficiently than the hybrid predictor without dynamic classification mechanism. To show performance improvements of our scheme, we simulate the SPECint95 benchmark set by using execution-driven simulator. The results show that our scheme effect reduce of 45% hardware cost and 16% prediction accuracy improvements comparing with the conventional hybrid prediction scheme and two-level value prediction scheme.

• Journal of Applied Reliability
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• v.10 no.3
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• pp.183-197
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• 2010

Web businesses are one of the most dynamic industries where lots of new business models are emerging while the other obsoleted ones are fading away almost every day. It is, therefore, difficult to establish a classification scheme for ever-changing web businesses. Previous researches on business models focus on classifying web businesses in one dimension which made some web sites difficult to fit into one category. We propose two dimensional classification scheme based on the means and the sources of revenue. The two dimensional classification provides more clear and broad perspectives of the web businesses and ways to identify web sites in combinations of several business models.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.171-174
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• 2004

Packet classification is an essential architectural component in implementing the quality-of-service (QoS) in today's Internet which provides a best-effort service to ail of its applications. Multiple header fields of incoming packets are compared against a set of rules in packet classification, the highest priority rule among matched rules is selected, and the packet is treated according to the action of the rule. In this Paper, we proposed a new packet classification scheme based on parallel multiple hashing on tuple spaces. Simulation results using real classifiers show that the proposed scheme provides very good performance on the required number of memory accesses and the memory size compared with previous works.

• Journal of the Korean Society for Railway
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• v.12 no.1
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• pp.175-182
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• 2009

Needs on ensuring compatibility and conformity of equipments that are used in logistics functions - such as packaging, transporting, loading/unloading and storing - are raised. This article presents a classification scheme for analyzing the interfacing characteristics of logistics equipments focusing on standardized pallets of unit load system. International and domestic classification systems are reviewed and analyzed; as a result several problems are issued. Methods to resolve the problems, to specify the attributes of logistics equipments and to represent the semantics among them using semantic web technology are proposed. This study could make it possible to examine the conformities of interfacing equipments automatically.