• Journal of Information Science Theory and Practice
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• v.2 no.3
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• pp.29-39
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• 2014

In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.3
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• pp.239-242
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• 2015

In this paper, we propose a walking assisting system for blind people using Android smartphone and Arduino board. In our proposed system, we use an Android smartphone case and an external ultrasonic sensor to detect the obstacles ahead. In this manner, blind people is able to aware unexpected objects by smartphone speakers or vibration functionality. In addition, the walking assisting system is also designed a notice system which will be triggered by built-in smartphone camera flash when blind people walk in some darkness place. The experimental results from real experiments on blind people have demonstrated the applicability of our walking assisting system, when it not only efficiently helps blind people avoid obstacles ahead but also possible traffic collisions in darkness condition.

• Smart Media Journal
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• v.6 no.3
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• pp.29-40
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• 2017

Lately weight for smartphone mounted to function for NFC is increasing, rapidly. Because of this, NFC related technology is made by many companies. We developed Gallery-Auction for security enhancements and new services of NFC-based 2 factor electronic payment system. Enhanced security features development of user authentication module through fingerprint recognition to apply FIDO authentication technology and developed electronic contract voice service of Gallery-Auction using TTS(Text to Speech). Therefore we enhanced convenient and simple authentication method and security through NFC mobile electronic payment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.649-651
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• 2021

In Korea, there are around 30,000 cardiac arrest patients annually. Gradually the number is increasing. Against this background, CPR education and publicity programs were expanded nationwide, but the rate of witness CPR by the general public was 4.4%, which is significantly lower than the 20%~70% rate in other countries. Therefore, in this paper, we analyzed the factors affecting the performance of CPR by witnesses who discovered cardiac arrest patients. Based on the results, an application planning and development study was conducted to provide users with correct cardiorespiratory response tips and step-by-step CPR guidelines to help users effectively assist in increasing the rate of CPR by general eyewitnesses.

• Industry Promotion Research
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• v.7 no.1
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• pp.81-87
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• 2022

This study used a method of comparing and analyzing various editions of Jeokcheonsu, and aims to confirm why different views have arisen on commentaries that differ according to the perspective of one original text, which interpretation is more valid among them. The biggest part of the misunderstanding of Myeongri theory in Jeokcheonsu is Kyeokguk theory. Jeokcheonsu does not set a high value on Kyeokguk, and it is highly regarded as the Myeongri classics that emphasizes Eokbuyongsin. However, as a result of classifying the original text by theory, we can see there are about 5 sentences that directly mention Eokbu theory, but 9 sentences that explain Kyeokguk theory and 15 sentences if we include the sentences that explain Jonggyeok and Hwagyeok. Even looking that metaphoric speech is mainly used, it is also clear that it's not a book written to be read by a beginner of Myeongri. This is Myeongri texts written to convey more profound logic and enlightenment to a person who has sufficient knowledge by having learned the principle of Myeongri. A single sentence of 'Jaegwaninsubunpyeonjeong Gyeomronsiksanggyeokgukjeong' would have been sufficient to explain the Kyeokguk theory, because it's written on the assumption of the reader's level. Among the later commentaries about the theory of Myeongri contained in Jeokcheosu, 4 persons'commentaries on the original text of 'Palkyeok', 'Gwansal', Sangkwan', 'Wolryeong', 'Saengsi', 'Cheongtak' related to Kyeokguk theory was compared and analyzed.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.309-328
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• 2022

This study empirically analyzed a Korean pre-trained language models (PLMs) designed for natural language generation. The performance of two PLMs - BART and GPT - at the task of abstractive text summarization was compared. To investigate how performance depends on the characteristics of the inference data, ten different document types, containing six types of informational content and creation content, were considered. It was found that BART (which can both generate and understand natural language) performed better than GPT (which can only generate). Upon more detailed examination of the effect of inference data characteristics, the performance of GPT was found to be proportional to the length of the input text. However, even for the longest documents (with optimal GPT performance), BART still out-performed GPT, suggesting that the greatest influence on downstream performance is not the size of the training data or PLMs parameters but the structural suitability of the PLMs for the applied downstream task. The performance of different PLMs was also compared through analyzing parts of speech (POS) shares. BART's performance was inversely related to the proportion of prefixes, adjectives, adverbs and verbs but positively related to that of nouns. This result emphasizes the importance of taking the inference data's characteristics into account when fine-tuning a PLMs for its intended downstream task.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.99-108
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• 2012

Many methods had been developed to improve the accuracy of extracting information from a vast amount of data. This paper combined a number of natural language processing methods such as NER (named entity recognition), sentence extraction, and part of speech tagging to carry out text analysis. The data source is comprised of texts obtained from the web using a domain-specific data extraction agent. A framework for the extraction of information from unstructured data was developed using the aforementioned natural language processing methods. We simulated the performance of our work in the extraction and analysis of texts for the detection of organizational structures. Simulation shows that our study outperformed other NER classifiers such as MUC and CoNLL on information extraction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3311-3317
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• 2010

This study compared South and North Korean broadcasting languages to measure the language differences due to the long segregation. This study would provide fundamental database on the language uses between South and North Korea. The KLIWC analyzed the text that was selected from news clips of South and North Korean broadcasting agencies. The results showed that North Korean languages were significantly different from South in terms of affective, cognitive, and social words. In addition, North Korean broadcasting used more person pronoun and a part of speech than South Korean broadcasting. Psychological interpretations were provided based on the language differences.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.198-206
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• 1996

Using eighteen text materials from various goners of present-day Japanese, we collected phonologically reduced forms frequently observed in conversational Japanese, and classified them in search of unified explanation of phonological reduction phenomena. We found 7,516 cases of reduced forms which we divided into 43 categories according to the types of phonological changes they have undergone. The general tendencies ale that deletion and fusion of a phoneme or an entire syllable takes place frequently, resulting in the decrease in the number of syllable. Typical examples frequently observed throughout the materials are : $~/noda/{\rightarrow}~/nda/,{\;}-/teiru/{\rightarrow}~/teru/,{\;}~/dewa/{\rightarrow}~/zja/,{\;}~/tesimau/{\rightarrow}~/cjau/$. From morphosyntactic point of view phonological reduction often occurs at the NP and VP morpheme boundaries. The following findings are drawn from phonological observations of reduction. (1) Vowels are more easily deleted than consonants. (2) Bilabials(/m/, /b/, and /w/ are the most likely candidates for deletion. (3) In a concatenation of vowels, closed vowels are absorbed into open vowels, or two adjacent vowels come to create another vowel, in which case reconstruction of the original sequence is not always predictable. (4) Alveolars are palatalized under the influence of front vowels. (5) Regressive assimilation takes place in a syllable starting with ill, changing the entire syllable into phonological choked sound or a syllabic nasal, depending on the voicing of following phoneme.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.77-82
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• 2002

운율은 음성의 초분절적인 면에 연관하는 음성의 한 성으로서 통상적으로 화자는 음성을 달하는 과정에서 청자의 이해를 돕기 위해 운율을 사용하게 된다. 본 논문은 이러한 운율을 이루는 성분 중의 하나인 운율구의 위치 예측에 대한 성능을 향상시키는 것에 그 목적을 둔다. 한국어 운율 정보에 대한 표기 방법 중의 하나인 K-ToBI를 기반으로 하여, 운율구의 경계와 그에 대한 레벨을 Break Indices 정보로서 나타내었고, 통계학 분야에서 제안된 Support Vector Machine(SVM)을 이용하여 시스템의 예측률 향상을 꾀하였다. 기존의 방법에서 사용된 트리 기반 모델을 이용하여 한국어 운율에 가장 많은 영향을 끼치는 언어 정보들을 추출하였고 이를 실험에 적용하였다. 기존의 트리 모델과 SVM 모델에 대한 예측률을 비교한 결과, 경계 유무 정보 예측과 4단계의 레벨을 가지는 경계 정보의 예측에서 모두 본 방법이 보다 높은 예측률을 보여 주어 본 연구에서 제시한 접근법이 운율구의 경계 정보를 예측하는 데에 있어 더욱 효과적인 접근법임을 실험적으로 입증하였다.