• Korean Journal of Cognitive Science
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• v.3 no.2
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• pp.311-328
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• 1992

The level and accuracy of English sentence that is generated by a man or machine translator are determined by the content of the verb dictionary and effective generation algorithm.The conventional English critiques is not adequate for foreigners because they do not have the verb dictionary including verb pattern or the important grammatical constraints. In this paper,Ipropose a structure of verb dictionary and an English sentence critique based on extended verb pattern that is useful to check and correct mistakes of English sentences generated by machine translator.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2435-2438
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• 2003

In this paper, we propose a Korean speech understanding model using dictionary and thesaurus. The proposed model search the dictionary for the same word with in input text. If it is not in the dictionary, the proposed model search the high level words in the high level word dictionary based on the thesaurus. We compare the probability of sentence understanding model with threshold probability, and we'll get the speech understanding rate. We evaluated the performance of the sentence speech understanding system by applying twenty questions game. As the experiment results, we got sentence speech understanding accuracy of 79.8％. In this case probability of high level word is 0.9 and threshold probability is 0.38.

• Language and Information
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• v.6 no.2
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• pp.33-55
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• 2002

This research aims at transforming the definition tort of an English-English-Korean Dictionary (EEKD) which is encoded in EST files for the purpose of publishing into a structured format for Lexical Data Base (LDB). The construction of LDB is very time-consuming and expensive work. In order to save time and efforts in building new lexical information, the present study tries to extract useful linguistic information from an existing printed dictionary. In this paper, the process of extraction and structuring of lexical information from a printed dictionary (EEKD) as a lexical resource is described. The extracted information is represented in XML format, which can be transformed into another representation for different application requirements.

• 중국학논총
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• no.65
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• pp.23-38
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• 2020

The dictionary is the most important tool for every Chinese learner to confirm the meaning and usage of words. Therefore, accuracy of headword's interpretation in the dictionary is crucial. This study aims to discuss the accuracy and the adequacy of headwords' interpretation in the Chinese-Korean dictionary through the Chinese corpus and Baidu. The scope of this study are 3000 words in the D3H1 region. According to the research results, the main problems of the vocabulary in this region can be divided into three categories: the first is the problem of lexical interpretation, the second is the problem of missing interpretation, and the third is other problems. In the D3H1 area, there are a total of 719 low-frequency vocabularies, and 54 headword's interpretations are not accurate or appropriate. This study is a detailed investigation and analysis of the problems of these 54 vocabularies.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.107-112
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• 2016

The Sejong Electronic(machine-readable) Dictionary, developed by the 21st century Sejong Plan, contains systematically organized information on Korean words. It helps to solve problems encountered in the electronic formatting of the still-commonly-used hard-copy dictionary. The Sejong Electronic Dictionary, however has a limitation relate to sentence structure and selection-restricted nouns. This paper discuses the limitations of word-sense disambiguation(WSD) that uses subcategorization information suggested by the Sejong Electronic Dictionary and generalized selection-restricted nouns from the Korean Lexico-semantic network. An alternative method that utilized semi-supervised learning, the chi-square test and some other means to make WSD decisions is presented herein.

• Journal of Auto-vehicle Safety Association
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• v.8 no.1
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• pp.19-25
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• 2016

As new car technology is developing, temporal interaction is needed in automotive. Rhythmic pattern is one of the practical examples of temporal interaction in vehicle. To recognize rhythmic pattern and its input medium, dictionary learning is applicable algorithm. In this paper, performance and memory requirement of the learning algorithm is tested and is sufficiently good for use this acoustic sound.

• Korean Journal of Oriental Medicine
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• v.18 no.1
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• pp.45-52
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• 2012

Objectives : Our study aims to provide a collaborative Internet terminology dictionary like Wikipedia, where about 30,000 concept terminologies with respect to traditional Korean medicine (TKM) are shared and TKM experts can edit the terminologies. Methods : The concept terminologies have been collected and refined for three years by the terminology management system, a custom-made software built upon the Oracle database, where each terminology is divided and normalized into one or more tables. The operation of Wikipedia depends on MediaWiki, a free and open source wiki software built upon the MySQL database. The database schema of our terminology management system is different from that of MediaWiki so that MediaWiki cannot used as our terminology dictionary. Thus, we propose a way to share and edit TKM terminologies with wiki-like user interface. Results : We devise a new terminology dictionary system to search and edit terminology upon the database of the terminology management system. The online terminology dictionary of TKM has the user interface and functions which is similar to Wikipedia to support collaborative works. Conclusions : Wikipedia is operated on MediaWiki which is can be downloaded and used freely under the GNU General Public License. However, there occur problems to use MediaWiki upon the legacy system. Thus, other wiki projects start, they should be considered.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.117-122
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• 2014

The minimal pairs mean the pairs that have same phonotactics except just one sound in the sequences cause different lexical items. This paper proposes the searching tool of minimal pairs for efficiency of phonological researches with minimal pairs. We suggest a guide to develop Korean minimal pair searching programs by comparing to other programs. Proposing tool has user-friendly interface, minimizing key inputs, for linguistics who are not fluent in computer programs. And it serves the function which classifies the words in dictionary for the detailed researches. And for efficiency, it increases speed of dictionary loading by separating syllables through Unicode analysis, and optimizes dictionary structure for searching efficiency. The searching algorithm gains in speed by hashing algorithm using syllable counts. In our tool, the speed is improved more than earlier version about 5 times at converting dictionary and about 3 times at searching.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1946-1963
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• 2014

Most background subtraction methods focus on dynamic and complex scenes without considering robustness against noise. This paper proposes a background subtraction algorithm based on dictionary learning and sparse coding for handling low light conditions. The proposed method formulates background modeling as the linear and sparse combination of atoms in the dictionary. The background subtraction is considered as the difference between sparse representations of the current frame and the background model. Assuming that the projection of the noise over the dictionary is irregular and random guarantees the adaptability of the approach in large noisy scenes. Experimental results divided in simulated large noise and realistic low light conditions show the promising robustness of the proposed approach compared with other competing methods.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1628-1636
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• 2004

Data compression techniques have been studied for decades because they saved space and time to reduce costs. The Lempel-Ziv 77 (LZ77) is a dictionary-based, lossless compression algorithm. The dictionary size of the LZ77 algorithm is fixed, and the performance of the algorithm is highly dependent on its dictionary size. In this paper, we suggest a dynamic LZ77 algorithm that changes its dictionary size during compression, and also we suggest a genetic algorithm to evolve the dictionary-resizing strategies. The suggested algorithm outperformed the original version up to about 16%.