• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.447-450
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• 2003

In this research, we propose an automatic knowledge acquisition and composite knowledge expression mechanism based on machine learning and relational database. Most of traditional approaches to develop a knowledge base and inference engine of expert systems were based on IF-THEN rules, AND-OR graph, Semantic networks, and Frame separately. However, there are some limitations such as automatic knowledge acquisition, complicate knowledge expression, expansibility of knowledge base, speed of inference, and hierarchies among rules. To overcome these limitations, many of researchers tried to develop an automatic knowledge acquisition, composite knowledge expression, and fast inference method. As a result, the adaptability of the expert systems was improved rapidly. Nonetheless, they didn't suggest a hybrid and generalized solution to support the entire process of development of expert systems. Our proposed mechanism has five advantages empirically. First, it could extract the specific domain knowledge from incomplete database based on machine learning algorithm. Second, this mechanism could reduce the number of rules efficiently according to the rule extraction mechanism used in machine learning. Third, our proposed mechanism could expand the knowledge base unlimitedly by using relational database. Fourth, the backward inference engine developed in this study, could manipulate the knowledge base stored in relational database rapidly. Therefore, the speed of inference is faster than traditional text -oriented inference mechanism. Fifth, our composite knowledge expression mechanism could reflect the traditional knowledge expression method such as IF-THEN rules, AND-OR graph, and Relationship matrix simultaneously. To validate the inference ability of our system, a real data set was adopted from a clinical diagnosis classifying the dermatology disease.

• Journal of Korean Society of Archives and Records Management
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• v.17 no.4
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• pp.127-154
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• 2017

Large-scale and complex disasters have frequently occurred all over the world recently, and they are repeated every year. Accordingly, the need for the systematic management and utilization of raw-data and processing information in the past has increased. For this purpose, this study proposed a construction strategy for disaster and safety record information resources archives based on automatic acquisition, which can be used as a hub for disaster and safety information. Based on local and foreign case studies, several consideration factors for building the archives are determined. Finally, this study proposed four steps for constructing the archives. These are as follows: 1) complete enumeration survey of the disaster and safety record information resources, 2) automatic acquisition possibility study, 3) selection of the resources for preservation, and 4) automatic acquisition of metadata. The construction of the archives proposed in this study will facilitate integrated management, sharing, and use of scattered information resources on disaster and safety.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.5
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• pp.1087-1091
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• 2007

This paper proposes a automatic korean lexical acquisition system which reflects the characteristics of human language acquisition. The proposed system automatically builds two kinds of lexicon, full-form lexicon and decomposition using Korean corpus as its input. As the experimental results using Korean Sejeong corpus of which size is 10 million Eojeols, the system acquired 2,097 full-form Eojeols and 3,488 morphemes. The accumulated frequency of the acquired full-form Eojeols covers the 38.63% of the input corpus and accuracy of morpheme acquisition is 99.87%.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.310-315
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• 1998

This study includes noise automatic inspection system for washing machine auto-transmission one of modern home necessary. We effort to find and certificate sound noisesource by sound power and sound intensity, and apply to frequency analysis in vibration related sound noise. Still more we have been studying to data acquisition and programming for MS VisualBasic version 5.0. System component is below. 1) Pentium PC for data acquisition. 2) DSO for noise acquisition. 3) S/W for comparison and decision. 4) I/F Board for data communication. Wave form data through the DSO are converting to ASCII code data. The ASCII code through binary converting S/W are to be decision fitness or the badness comparison S/W. Finally, we will making noise monitoring system and automatic inspection system.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.375-384
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• 2007

This paper describes a method for automatic acquisition of wide-coverage treebank-based deep linguistic resources for Japanese, as part of a project on treebank-based induction of multilingual resources in the framework of Lexical-Functional Grammar (LFG). We automatically annotate LFG f-structure functional equations (i.e. labelled dependencies) to the Kyoto Text Corpus version 4.0 (KTC4) (Kurohashi and Nagao 1997) and the output of of Kurohashi-Nagao Parser (KNP) (Kurohashi and Nagao 1998), a dependency parser for Japanese. The original KTC4 and KNP provide unlabelled dependencies. Our method also includes zero pronoun identification. The performance of the f-structure annotation algorithm with zero-pronoun identification for KTC4 is evaluated against a manually-corrected Gold Standard of 500 sentences randomly chosen from KTC4 and results in a pred-only dependency f-score of 94.72%. The parsing experiments on KNP output yield a pred-only dependency f-score of 82.08%.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.6
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• pp.9-18
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• 2000

This study includes noise automatic inspection system for washing machine auto-transmission one of modern home necessary. We effort to find and certificate sound noise source by sound power and sound intensity, and apply to frequency analysis in vibration related sound noise. still more we have been studying to data acquisition and programming for MS VisualBasic version 5.0. System component is below. 1) Pentium PC or data acquisition. 2) DSO for noise acquisition. 3)S/W for comparison and decision. 4) I/F Board for data communication. Wave form data through the DSO are converting to ASCII code data. The ASCII code through binary converting S/W. Finally we will making noise monitoring system and automatic inspection system.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.2
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• pp.184-193
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• 2015

This paper proposes a cost-efficient and automatic method for large data acquisition from a test chip without expensive equipment to characterize random process variation in an integrated circuit. Our method requires only a test chip, a personal computer, a cheap digital-to-analog converter, a controller and multimeters, and thus large volume measurement can be performed on an office desk at low cost. To demonstrate the proposed method, we designed a test chip with a current model logic driver and an array of 128 current mirrors that mimic the random process variation of the driver's tail current mirror. Using our method, we characterized the random process variation of the driver's voltage due to the random process variation on the driver's tail current mirror from large volume measurement data. The statistical characteristics of the driver's output voltage calculated from the measured data are compared with Monte Carlo simulation. The difference between the measured and the simulated averages and standard deviations are less than 20% showing that we can easily characterize the random process variation at low cost by using our cost-efficient automatic large data acquisition method.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.1082-1087
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• 1994

A set of text database is indispensable to the probabilistic models for speech recognition, linguistic model, and machine translation. We introduce an environment to canstruct text databases : an automatic tagging system and a set of tools for lexical knowledge acquisition, which provides the facilities of automatic part of speech recognition and guessing.

• The Journal of Korean Association of Computer Education
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• v.13 no.1
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• pp.65-73
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• 2010

This study offered lexical knowledge acquisition model of unsupervised learning method in order to overcome limitation of lexical knowledge hand building manual of supervised learning method for research of natural language processing. The offered model obtains the lexical knowledge from the lexical entry which was given by inputting through the process of vectorization, clustering, lexical knowledge acquisition automatically. In the process of obtaining the lexical knowledge acquisition of model, some parts of lexical knowledge dictionary which changes in the number of lexical knowledge and characteristics of lexical knowledge appeared by parameter changes were shown. The experimental results show that is possibility of automatic building of Machine-readable dictionary, because observed to the number of lexical class information cluster collected constant. also building of lexical ditionary including left-morphosyntactic information and right-morphosyntactic information is reflected korean characteristic.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.146-154
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• 2007

AutoCor is a method for the automatic acquisition and classification of corpora of documents in closely-related languages. It is an extension and enhancement of CorpusBuilder, a system that automatically builds specific minority language corpora from a closed corpus, since some Tagalog documents retrieved by CorpusBuilder are actually documents in other closely-related Philippine languages. AutoCor used the query generation method odds ratio, and introduced the concept of common word pruning to differentiate between documents of closely-related Philippine languages and Tagalog. The performance of the system using with and without pruning are compared, and common word pruning was found to improve the precision of the system.