• ETRI Journal
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• v.29 no.4
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• pp.527-529
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• 2007

In this paper, a decision-tree-based Markov model for phrase break prediction is proposed. The model takes advantage of the non-homogeneous-features-based classification ability of decision tree and temporal break sequence modeling based on the Markov process. For this experiment, a text corpus tagged with parts-of-speech and three break strength levels is prepared and evaluated. The complex feature set, textual conditions, and prior knowledge are utilized; and chunking rules are applied to the search results. The proposed model shows an error reduction rate of about 11.6% compared to the conventional classification model.

• Proceedings of the KSEEG Conference
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• 2007.04a
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• pp.127-129
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• 2007

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• Journal of the Korea Safety Management & Science
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• v.4 no.1
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• pp.27-36
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• 2002

This paper describes "the remote automatic diagnosis and repair system which automatically reads the problems such as "out of order" occurred on equipment at customer's equipment from a remote computer center using HTTP(hyper text transfer protocol). It shows the scheme of the network configurations and features of the system. In addition, a way to implement the overall system, the specific functions of unit, and the operational specifications between the center's computer and customer's computer are also presented.also presented.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.227-228
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• 2019

This study examines the features of Korean EFL students' letter writing at a university in Korea. The data comprised interviews and examples of letter writing. The findings revealed that students engaged in unique ways in which they oriented their meaning-making to broad views concerning rhetorics and components. Students' approaches involved a particular context and the recontextualized English formal letter, which reflects their textual interactions in writing. This paper concludes that specific discourse communities, life-world, and learning purposes impact on students' English writing.

• The Journal of Society for e-Business Studies
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• v.19 no.2
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• pp.95-108
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• 2014

Opinion Mining is one of the application domains of text mining which extracting opinions from documents, and much researches are currently underway. Most of related researches focused on the sentiment classification which classifies the documents into positive/negative opinions. However, there is a little interest in extracting the features characterizing the individual product. In this paper, we propose the technique classifying the opinion documents according to the product features, and selecting the those features characterizing each product. In the proposed method, we utilize the document clustering technique and develope a new algorithm for evaluating the similarity between documents. In addition, through experiments, we prove the usefulness of proposed method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.33-42
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• 2016

Recently, an environment in which public opinions are expressed about various areas is expanded around SNSs or internet potals, thus, opinion documents get bigger rapidly. Under these circumstances, it is essential to utilize automatic summarization techniques for understanding whole contents of large opinion documents. However, it is hard to summarize efficiently those documents with traditional text summarization technologies since the documents include subject expressions as well as features of targets objects. Proposed method in this paper defines features of opinion documents, and designed to retrieve representative sentences expressing opinions of those features. In addition, through experiments, we prove the usefulness of proposed method.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.45-54
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• 2009

In this paper we propose a new approach that recognizes the similar categories by weighting distinctive features. The approach is based on the PLSA that is one of the effective methods for the object categorization. PLSA is introduced from the information retrieval of text domain. PLSA, unsupervised method, shows impressive performance of category recognition. However, it shows relatively low performance for the similar categories which have the analog distribution of the features. In this paper, we consider the effective object categorization for the similar categories by weighting the mainly distinctive features. We present that the proposed algorithm, weighted PLSA, recognizes similar categories. Our method shows better results than the standard PLSA.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.16-25
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• 2018

The talking head (TH) indicates an utterance face animation generated based on text and voice input. In this paper, we propose the generation method of TH with facial expression and intonation by speech input only. The problem of generating TH from speech can be regarded as a regression problem from the acoustic feature sequence to the facial code sequence which is a low dimensional vector representation that can efficiently encode and decode a face image. This regression was modeled by bidirectional RNN and trained by using SAVEE database of the front utterance face animation database as training data. The proposed method is able to generate TH with facial expression and intonation TH by using acoustic features such as MFCC, dynamic elements of MFCC, energy, and F0. According to the experiments, the configuration of the BLSTM layer of the first and second layers of bidirectional RNN was able to predict the face code best. For the evaluation, a questionnaire survey was conducted for 62 persons who watched TH animations, generated by the proposed method and the previous method. As a result, 77% of the respondents answered that the proposed method generated TH, which matches well with the speech.

• Journal of the Korean Society of Safety
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• v.36 no.5
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• pp.52-60
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• 2021

As the prevention of fatal accidents is considered an essential part of social responsibilities, both government and individual have devoted efforts to mitigate the unsafe conditions and behaviors that facilitate accidents. Several studies have analyzed the factors that cause fatal accidents and compared them to those of non-fatal accidents. However, studies on mathematical and systematic analysis techniques for identifying the features of fatal accidents are rare. Recently, various industrial fields have employed machine learning algorithms. This study aimed to apply machine learning algorithms for the classification of fatal and non-fatal accidents based on the features of each accident. These features were obtained by text mining literature on accidents. The classification was performed using four machine learning algorithms, which are widely used in industrial fields, including logistic regression, decision tree, neural network, and support vector machine algorithms. The results revealed that the machine learning algorithms exhibited a high accuracy for the classification of accidents into the two categories. In addition, the importance of comparing similar cases between fatal and non-fatal accidents was discussed. This study presented a method for classifying accidents using machine learning algorithms based on the reports on previous studies on accidents.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.73-80
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• 2019

This paper tried to investigate the features of French garden pavillons (jardin pavillons) in the 17th and 18th centuries, in which the royal built them, publicly enjoying culture or privately having a refuge. The scope of the garden pavilions covered those associated with a pleasure place that accommodated performances, dancing, and dinners. They included not only rustic, Chinese, Turkish and Gothic pavilions but also grottos, nymphaeums, and artificial ruins built for banquets and festivals. This paper identified the features of the 17th and 18th century French garden pavilions as follows: Those pavilions firstly established French Neoclassicism, secondly applied the techniques of pastiche, thirdly reflected women's influence, and lastly revealed the short cycles of their vicissitudes. In conclusion this study, with the summary of the main text, explained the influence of the French pavilions on Europe and America.