• Journal of the Korean Society for Library and Information Science
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• v.32 no.4
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• pp.249-274
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• 1998

It is the analyses of replies showed n the questionnaire consisted of four kinds of matters to see level of knowledge among SELIS (SEoul Women's University Library and Information System) OPAC users of keyword/boolean search. The result of this analyses is : in SELIS search, users who prefer keyword search than any other, who satisfy work of retrieval by means of boolean operator, and who think it easier, show lusher level of knowledge than those who deny it in the questionnaire. Knowledges Presented in the survey are ; characteristics of keyword search, single or double keys, using boolean operator in keyword, knowledge of index, knowledge of stop list, uncontrolled term. keyword search technique, right truncation, correct application of boolean logic operator, and selecting major subject in keyword browsing. The above mentioned knowledges will work as important factors n keyword/boolean search, OPAC. For successful search it requires conceptional knowledge of information retrieval processing, or inquiry word transformation how to search required information, and semantic ability to get result questioned In the given system, when and how to apply the characteristics of the system, and scientific record for user's inquiry, or fundamental computer technology and syntax knowledge to make search word in detail. But so far now important knowledge considered as user's online index search, has been emphasized on knowledge of scientific record, and has been lag of semantic and conceptional knowledge. So, it is recommendable for online index user to train to concentrate semantic knowledge, syntax ability, and conceptional knowledge, rather than scientific technique too much.

• Journal of Internet Computing and Services
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• v.21 no.3
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• pp.123-131
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• 2020

Along with the rapid development of artificial intelligence technology, natural language processing, which deals with human language, is also actively studied. In particular, BERT, a language model recently proposed by Google, has been performing well in many areas of natural language processing by providing pre-trained model using a large number of corpus. Although BERT supports multilingual model, we should use the pre-trained model using large amounts of Korean corpus because there are limitations when we apply the original pre-trained BERT model directly to Korean. Also, text contains not only vocabulary, grammar, but contextual meanings such as the relation between the front and the rear, and situation. In the existing natural language processing field, research has been conducted mainly on vocabulary or grammatical meaning. Accurate identification of contextual information embedded in text plays an important role in understanding context. Knowledge graphs, which are linked using the relationship of words, have the advantage of being able to learn context easily from computer. In this paper, we propose a system to extract Korean contextual information using pre-trained BERT model with Korean language corpus and knowledge graph. We build models that can extract person, relationship, emotion, space, and time information that is important in the text and validate the proposed system through experiments.

• The Journal of Korean Association of Computer Education
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• v.11 no.5
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• pp.1-8
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• 2008

Computers are played an important tole of knowledge-information society in 21C. Computer education have made successful progresses since the 7th curricula have one class of ICT per week. However, public schools have instructed computer literacy education teaching only how to use application software. To give useful knowledges students could use for several decades, we need to have them to concentrate on education to information logical thinking power rather than simple manipulation of application softwares. However, teachers don't understand well about the "Understanding of Information Processing". In this paper, we carried out a survey that how much teachers understand about the information processing comprehension among the information and communication technology guide. We also state problems and propose improvement plan.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1171-1174
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• 1993

A promising approach to get the benefits of neural networks and fuzzy logic is to combine them into an integrated system to merge the computational power of neural networks and the representation and reasoning properties of fuzzy logic. In this context, this paper presents a fuzzy neural network which is able to code fuzzy knowledge in the form of it-then rules in its structure. The network also provides an efficient structure not only to code knowledge, but also to support fuzzy reasoning and information processing. A learning scheme is also derived for a class of membership functions.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.193-202
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• 2017

Development of Intelligent Systems involves effective integration of large-scaled knowledge processing and understanding, human-machine interaction, and intelligent services. Especially, in our project for development of a self-growing knowledge-based system with inference methodologies utilizing the big data technology, we are building a platform called WiseKB as the central knowledge base for storing massive amount of knowledge and enabling question-answering by inferences. WiseKB thus requires an effective methodology to analyze diverse requirements convoluted with the integration of various components of knowledge representation, resource management, knowledge storing, complex hybrid inference, and knowledge learning, In this paper, we propose an integrated requirement analysis method that blends the traditional sequential method and the iterative-incremental method to achieve an efficient requirement analysis for large-scale systems.

• Korean Institute of Interior Design Journal
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• v.24 no.1
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• pp.104-114
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• 2015

The library means to children a place where they find information necessary for them among a variety of knowledge and information to address their intellectual curiosity, which makes their lives wise and mature. There are not enough research materials understanding children's cognitive systems and behaviors in studies of a children's library with this necessity. This study divided and analyzed the behaviors of children, who were users into three types of reading in terms of information processing. First, it observed the types of reading depending on the stage of their cognitive development; Second, it analyzed the patterns of their behaviors through plays; and lastly, it presented the phases of their behaviors depending on the degree of an assistant's intervention. As a result of the study, the sensory system used and the space preferred differed depending on the stage of their cognition; there were differences in the patterns of their behaviors in each age group depending on the type of play; and there were differences in the children's ability of information processing depending on the assistant's ability. It is anticipated that there will be improvements of children's reading ability at the reading room in a better environment if the three types are considered in terms of information processing.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.569-584
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• 2016

In this paper, we present a spatial knowledge extractor implemented in Hadoop MapReduce parallel, distributed computing environment. From a large spatial dataset, this knowledge extractor automatically derives a qualitative spatial knowledge base, which consists of both topological and directional relations on pairs of two spatial objects. By using R-tree index and range queries over a distributed spatial data file on HDFS, the MapReduce-enabled spatial knowledge extractor, MRSPAKE, can produce a web-scale spatial knowledge base in highly efficient way. In experiments with the well-known open spatial dataset, Open Street Map (OSM), the proposed web-scale spatial knowledge extractor, MRSPAKE, showed high performance and scalability.

• Journal of the Korean Society for information Management
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• v.19 no.4
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• pp.96-111
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• 2002

A lot of accumulated data of many quantity exist within a institution or an organization, but most data is remained in form of standardization as each institution or organization. There are difficulty in exchange and share of information. New concept of knowledge information resource management to overcome this disadvantage was introduced, and the digitization of knowledge information resources to share and manage accumulated data is been doing. Specially, in science technic or education scholarship it, the tendency that importing XML to process necessary data to exchange and share of knowledge information resources structurally, and limitation of back for search and indexing or reusability is happened according as expression of great many mathematics used inside electron document of these sphere is processed to nonstructural data of image or text and so on. There is interest converged in processing of mathematics that use MathML to overcome this, and we require the solution to be able to process MathML easily and efficiently on structural document. In this paper, designed and implemented of XML document editing system which easy structural process of electronic document for knowledge information resources, and create and express MathML easily on structural document without expert knowledge about MathML.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.123-131
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• 2012

The requirements for computational resources to perform the structural analysis are increasing rapidly. The size of the current analysis problems that are required from practical industry is typically large-scale with more than millions degrees of freedom (DOFs). These large-scale analysis problems result in the requirements of high-performance analysis codes as well as hardware systems such as supercomputer systems or cluster systems. In this paper, the pre- and post-processing system for supercomputing based large-scale structural analysis is presented. The proposed system has 3-tier architecture and three main components; geometry viewer, pre-/post-processor and supercomputing manager. To analyze large-scale problems, the ADVENTURE solid solver was adopted as a general-purpose finite element solver and the supercomputer named 'tachyon' was adopted as a parallel computational platform. The problem solving performance and scalability of this structural analysis system is demonstrated by illustrative examples with different sizes of degrees of freedom.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.688-710
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• 2016

Our approach permits to capitalize the expert's knowledge as business rules by using an agent-based platform. The objective of our approach is to allow experts to manage the daily evolutions of business domains without having to use a technician, and to allow them to be implied, and to participate in the development of the application to accomplish the daily tasks of their work. Therefore, the manipulation of an expert's knowledge generates the need for information security and other associated technologies. The notion of cryptography has emerged as a basic concept in business rules modeling. The purpose of this paper is to present a cryptographic algorithm based approach to integrate the security aspect in business rules modeling. We propose integrating an agent-based approach in the framework. This solution utilizes a security agent with domain ontology. This agent applies an encryption/decryption algorithm to allow for the confidentiality, authenticity, and integrity of the most important rules. To increase the security of these rules, we used hybrid cryptography in order to take advantage of symmetric and asymmetric algorithms. We performed some experiments to find the best encryption algorithm, which provides improvement in terms of response time, space memory, and security.