• Journal of Information Technology Applications and Management
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• 제10권2호
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• pp.33-41
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• 2003

It is not easy to find desired information in the world wide web. In this research, we introduce a notion of concept network that is useful in finding information if it is used in search engines that are specialized in domains such as medicine, law or engineering. The concept network that we propose is a network in which nodes represent significant concepts in the domain, and links represent relationships between the concepts. We may use the concept network constructor as a preprocessor to speci-alized search engines. When user enters a target word to find information, our system generates and displays a concept network in which nodes are con-cepts that are closely related with the target word. By reviewing the network, user may confirm that the target word is properly selected for his intention, otherwise he may replace the target word with better ones discovered in the network. In this research, we propose a detailed method to construct concept net-work, implemented a prototypical system that constructs concept networks, and illustrate its usefulness by demonstrating a practical case.

• Journal of Information Technology Applications and Management
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• 제23권2호
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• pp.11-28
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• 2016

In this paper, we proposed a dictionary extension and a ternary decomposition technique to improve the effectiveness of Khmer word segmentation. Most word segmentation approaches depend on a dictionary. However, the dictionary being used is not fully reliable and cannot cover all the words of the Khmer language. This causes an issue of unknown words or out-of-vocabulary words. Our approach is to extend the original dictionary to be more reliable with new words. In addition, we use ternary decomposition for the segmentation process. In this research, we also introduced the invisible space of the Khmer Unicode (char\u200B) in order to segment our training corpus. With our segmentation algorithm, based on ternary decomposition and invisible space, we can extract new words from our training text and then input the new words into the dictionary. We used an extended wordlist and a segmentation algorithm regardless of the invisible space to test an unannotated text. Our results remarkably outperformed other approaches. We have achieved 88.8%, 91.8% and 90.6% rates of precision, recall and F-measurement.

• 한국수학교육학회지시리즈A:수학교육
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• 제38권1호
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• pp.77-85
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• 1999

In this paper, we analyze strategies and error patterns in solving word problems of linear equation for middle school students. From a test conducted to the sampled 106 second grade middle school students, we obtain the following results: (1)The most difficult types of word problem are velosity and density related problems. The second one is length related problems and the easist one is number related problems. (2)Regardless of the types of word problem, the most familiar strategy is the constructing algebraic equations. However, the most successful strategy is the trial and error. (3)Most likely error patterns are the use of inadequate formulas and wrong trial and errors. Based on these results, a teaching program with various schema is developed and shown to be effective for mid level students in classroom.

• 말소리와 음성과학
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• 제3권3호
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• pp.63-68
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• 2011

This study investigates how Korean students employ acoustic-phonetic cues in perceiving word boundaries of near-homophonous English phrases. For this study, 60 Korean college students participated in the experiment of discriminating word boundaries for 42 pairs of stimuli comprising the allophonic cues of aspiration and glottal stop. Results were analysed in terms of the correctness of responses and the correlation between correctness and confidence. Results showed that stimuli pairs of the glottal stop cue give a higher correctness but those of aspiration a relatively lower correctness. Comparison of the results of this study with those of the previous studies of English and Japanese speakers showed that Korean and Japanese speakers of English give a substantially lower correctness than native speakers of English, while Korean learners of English as a foreign language provide a lower correctness than Japanese speakers of English as a second language.

• 전자공학회논문지B
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• 제33B권10호
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• pp.98-106
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• 1996

This paper proposes an algorithm for analyzing illocutionary force type (IfT)s in a dialogue, based on the context and modal information in the ending of a word. In korean, the variation of an illocutionary force type that represents a speaker's intention frequently occurs at the ending of a word, according to the type of modal information. And in an analysis of speech acts, the modal information illocutionary force types. In this paper, we analyze real dialogue dta, classify the types of illocutionary forces, perform the manual tagging of IFTs and show the freqency of each IFT's occurence. And we also propose an algorithm to extract IFTs, based on the relationship between the analyzed IFTs and the endings of a word. And we use this proposed algorithm to make an experiment on dialogue data and show its efficiency.

• 한국음향학회지
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• 제30권8호
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• pp.428-435
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• 2011

Many isolated word recognition systems may generate irrelevant words for recognition results because they use only acoustic information or small amount of language information. In this paper, I propose word similarity that is used for selecting (or removing) less common words from candidates by applying Levenshtein distance. Word similarity is obtained by using positional accuracy that reflects the frequency information along to character's alignment information. This paper also discusses various improving techniques of selection of disparate words. The methods include different loss values, phone accuracy based on confusion information, weights of candidates by ranking order and partial comparisons. Through experiments, I found that the proposed methods are effective for removing heterogeneous words without loss of performance.

• 말소리와 음성과학
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• 제2권4호
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• pp.153-161
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• 2010

Many isolated word recognition systems may generate non-similar words for recognition candidates because they use only acoustic information. The previous study [1,2] investigated several techniques which can exclude non-similar words from N-best candidate words by applying Levenstein distance measure. This paper discusses the various improving techniques of removing non-similar recognition results. The mentioned methods include comparison penalties or weights, phone accuracy based on confusion information, weights candidates by ranking order and partial comparisons. Through experimental results, it is found that some proposed method keeps more accurate recognition results than the previous method's results.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2003년도 추계공동학술대회
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• pp.721-727
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• 2003

This study designed and implemented a system to extract of vowel from a word. The system is comprised of a voice feature extraction module and a neutral network module. The voice feature extraction module use a LPC(Linear Prediction Coefficient) model to extract a voice feature from a word. The neutral network module is comprised of a learning module and voice recognition module. The learning module sets up a learning pattern and builds up a neutral network to learn. Using the information of a learned neutral network, a voice recognition module extracts a vowel from a word. A neutral network was made to learn selected vowels(a, eo, o, e, i) to test the performance of a implemented vowel extraction recognition machine. Through this experiment, could confirm that speech recognition module extract of vowel from 4 words.

• 한국멀티미디어학회논문지
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• 제24권10호
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• pp.1391-1402
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• 2021

This paper focuses use context-sensitive spelling error correction using generative adversarial network. Generative adversarial network[1] are attracting attention as they solve data generation problems that have been a challenge in the field of deep learning. In this paper, sentences are generated using word embedding information and reflected in word distribution representation. We experiment with DCGAN[2] used for the stability of learning in the existing image processing and D2GAN[3] with double discriminator. In this paper, we experimented with how the composition of generative adversarial networks and the change of learning corpus influence the context-sensitive spelling error correction In the experiment, we correction the generated word embedding information and compare the performance with the actual word embedding information.

• 한국멀티미디어학회논문지
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• 제24권1호
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• pp.106-116
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• 2021

To increase the quality of the system in the subjective-type question grading and document classification, we need the paragraph detection. But it is not easy because it is accompanied by semantic analysis. Many researches on the paragraph detection solve the detection problem using the word based clustering method. However, the word based method can not use the order and dependency relation between words. This paper suggests the paragraph detection system using syntactic-semantic relation between words with the Korean syntactic-semantic analysis. This system is the hybrid system of word based, concept based, and syntactic-semantic tree based detection. The experiment result of the system shows it has the better result than the word based system. This system will be utilized in Korean subjective question grading and document classification.