• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.3972-3988
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• 2020

Existing methods always rely on statistical features to extract local words for microblog user geolocation. There are many non-local words in extracted words, which makes geolocation accuracy lower. Considering the statistical and semantic features of local words, this paper proposes a microblog user geolocation method by extracting local words based on word clustering and wrapper feature selection. First, ordinary words without positional indications are initially filtered based on statistical features. Second, a word clustering algorithm based on word vectors is proposed. The remaining semantically similar words are clustered together based on the distance of word vectors with semantic meanings. Next, a wrapper feature selection algorithm based on sequential backward subset search is proposed. The cluster subset with the best geolocation effect is selected. Words in selected cluster subset are extracted as local words. Finally, the Naive Bayes classifier is trained based on local words to geolocate the microblog user. The proposed method is validated based on two different types of microblog data - Twitter and Weibo. The results show that the proposed method outperforms existing two typical methods based on statistical features in terms of accuracy, precision, recall, and F1-score.

• Speech Sciences
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• v.7 no.2
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• pp.37-50
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• 2000

This paper describes a test of everyday speech understanding ability, in which a listener's utilization of the context-situational information of speech is assessed, and is compared with the utilization of acoustic-phonetic information. The test items are sentences which are presented in a babble type of noise, and the listener response is the key word in the sentence. The key words are always two-syllabic nouns and the questioning sentences are added to obtain the responding key words. Two types of sentences are used. One is the high-predictable sentences for which the key word is somewhat predictable from the context. The other is the low-predictable sentences for which the key-word cannot be predicted from the context. Both types are included in six 40-item forms of the test, which are balanced for intelligibility, key-word familiarity and predictability, phonetic content, and length. Performance of normally hearing listeners shows significantly different functions for various signal-to-noise ratios. The potential applications of this test, particularly in the assessment of speech understanding ability in the hearing impaired, are discussed.

• The Korean Journal of Emergency Medical Services
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• v.24 no.1
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• pp.85-92
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• 2020

Purpose: The purpose of this study was to analyze the English abstract key words found within the Korea Society of Emergency Medical Services journal using text mining techniques to determine the adherence of these terms with Medical Subject Headings (MeSH) and identify key word trends. Methods: We analyzed 212 papers that were published from 2012 to 2019. R software, web scraping, and frequency analysis of key words were conducted using R's basic and text mining packages. Additionally, the Word Clouds package was used for visualization. Results: The average number of key words used per study was 3.9. Word cloud visualization revealed that CPR was most prominent in the first half and emergency medical technician was most frequently used during the second half. There were a total of 542 (64.9%) words that exactly matched the MeSH listed words. A total of 293 (35%) key words did not match MeSH listed words. Conclusion: Researchers should obey submission rules. Further, journals should update their respective submission rules. MeSH key words that are frequently cited should be suggested for use.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.165-172
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• 2010

There are two method of error correction in vocabulary recognition system. one error pattern matting base on method other vocabulary mean pattern base on method. They are a failure while semantic of key-word problem for error correction. In improving, in this paper is propose system of key-word error correction using algorithm of syllable restoration. System of key-word error correction by processing of semantic parse through recognized phoneme meaning. It's performed restore by algorithm of syllable restoration phoneme apply fluctuation before word. It's definitely parse of key-word and reduced of unrecognized. Find out error correction rate using phoneme likelihood and confidence for system parse. When vocabulary recognition perform error correction for error proved vocabulary. system performance comparison as a result of recognition improve represent 2.3% by method using error pattern learning and error pattern matting, vocabulary mean pattern base on method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.348-353
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• 2004

Development of an efficient and secure payment system is prerequisite for the construction of electronic payment mechanism in mobile environment. Since current PayWord protocol system generates vendor's certificate for each transaction, it requires lot of operation for transaction. In this paper, we use a session key generated by ID-based tripartite Key agreement protocol which use an Elliptic Curve Cryptosystem over finite field $F_{q}$ for transactions. Therefore, our protocol reduces algorithm operations. In particular, proposed protocol using ID-based public key cryptosystem has the advantages over the existing systems in speed and it is more secure in Man-in-the-middle attacks and Forward secrecy.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.3
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• pp.109-119
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• 2019

The purpose of this study is to examine fashion trends and the direction of the four fashion collections by analyzing the design key-words of the four major international fashion collections in 2018. The data of this study was collected by extracting the key-words from Marie Claire Korea in 2018, with the total of the collected data numbering 2,144. The data was analyzed by text mining using the R program and word-cloud, and a co-occurrence network analysis was conducted. The results of this study are as follows: First, the key-words of fashion collection designs in 2018 were fringe and ruffle detail, silk and denim fabric, vivid color, stripe and check pattern, pants suit item, and oversized silhouette, focusing on romanticism and sport. Second, seasonal characteristics of the fashion collections were pastel colors in S/S, primary and vivid colors in F/W. Details were embroidery and cutouts in S/S, patchwork and fringe in F/W. Third, the design trends of the four major fashion collections were presented in the Paris collection: stripes, check patterns, embroidery, lace, tailoring, draping, romanticism, and glamor. In the Milan collection, checks, prints, denim, and minidresses reflected sport and romanticism. The London collection included fringe, ruffles, floral patterns, flower patterns, and romanticism. The New York collections included vivid colors, neon colors, pastel colors, oversize silhouettes, bodysuits, and long dresses.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1586-1593
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• 2010

Vocabulary recognition error correction method has probabilistic pattern matting and dynamic pattern matting. In it's a sentences to based on key-word by semantic analysis. Therefore it has problem with key-word not semantic analysis for morphological changes shape. Recognition rate improve of vocabulary unrecognized reduced this paper is propose. In syllable restoration algorithm find out semantic of a phoneme recognized by a phoneme semantic analysis process. Using to sentences restoration that morphological analysis and morphological analysis. Find out error correction rate using phoneme likelihood and confidence for system parse. When vocabulary recognition perform error correction for error proved vocabulary. system performance comparison as a result of recognition improve represent 2.0% by method using error pattern learning and error pattern matting, vocabulary mean pattern base on method.

• Journal of Korea Trade
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• v.26 no.8
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• pp.37-57
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• 2022

Purpose -International diplomacy is key for the cohesive economic growth of countries around the world. This study aims to identify the major topics discussed and make sense of word pairs used in sentences by Chinese senior leaders during their diplomatic visits. It also compares the differences between key topics addressed during diplomatic visits to developed and developing countries. Design/methodology - We employed three methods: word frequency, co-word, and semantic network analysis. Text data are crawling state and official visit news released by the Ministry of Foreign Affairs of the People's Republic of China regarding diplomatic visits undertaken from 2015-2019. Findings - The results show economic and diplomatic relations most prominently during state and official visits. The discussion topics were classified according to nine centrality keywords most central to the structure and had the maximum influence in China. Moreover, the results showed that China's diplomatic issues and strategies differ between developed and developing countries. The topics mentioned in developing countries were more diverse. Originality/value - Our study proposes an effective approach to identify key topics in Chinese diplomatic talks with other countries. Moreover, it shows that discussion topics differ for developed and developing countries. The findings of this research can help researchers conduct empirical studies on diplomacy relationships and extend our method to other countries. Additionally, it can significantly help key policymakers gain insights into negotiations and establish a good diplomatic relationship with China.

• 프린팅코리아
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• s.64
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• pp.138-138
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• 2007

• Journal of KIISE:Information Networking
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• v.31 no.4
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• pp.405-413
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• 2004

Design an efficient and secure electronic payment system is important for M-Commerce. In this paper, we propose an efficient Micro-Payment Protocol that allows multiple transactions using ID-based public key cryptosystem. Current PayWord system requires to generate certificate of the vendor for each transaction. In this paper, we use a session key instead of certificate key generated by Weil Pairing which use an Elliptic Curve Cryptosystem over finite field $F_q$ for transactions Therefore, it is more secure in Known key attacks as well as Man-in-the-middle attacks.