• The Journal of the Korea Contents Association
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• v.21 no.10
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• pp.21-37
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• 2021

This study investigated the intellectual structure of the latest trends in Korean addiction research in the social sciences. A network analysis of keywords with co-word occurrence was performed on 172 papers from the KCI database based on the data from the year of 2019, and a total of 432 keywords were extracted. The network analysis was performed using several programs: Bibexcel, COOC, WNET, and NodeXL. As a result of the study, keywords related to addiction type, study subjects, research methods, and research variables were found, and a total of 20 clusters were identified. Furthermore, to identify and measure weighted networks, the relationships between each keyword were explored and discussed in detail through a network analysis of global centralities, local centralities, and betweenness centralities. The study indicated that the latest issues were focused on smartphone addiction and provided implications for the future research and practice that fields and topics of relationship addiction, food addiction, and work addiction should be more considered. Further, the study discussed the relationship between drug addiction-crime, alcohol addiction-family, and gambling addiction-motivation and the necessity of qualitative study.

• Journal of KIISE:Software and Applications
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• v.37 no.10
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• pp.788-801
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• 2010

Advancing of mobile device is remarkable, so the research on mobile input device is getting more important issue. There are lots of input devices such as keypad, QWERTY keypad, touch and speech recognizer, but they are not as convenient as typical keyboard-based desktop input devices so input strings usually contain many typing errors. These input errors are not trouble with communication among person, but it has very critical problem with searching in database, such as dictionary and address book, we can not obtain correct results. Especially, Hangeul has more than 10,000 different characters because one Hangeul character is made by combination of consonants and vowels, frequency of error is higher than English. Generally, suffix tree is the most widely used data structure to deal with errors of query, but it is not enough for variety errors. In this paper, we propose fast approximate Korean word searching system, which allows variety typing errors. This system includes several algorithms for applying general approximate string searching to Hangeul. And we present profanity filters by using proposed system. This system filters over than 90% of coined profanities.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.11-39
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• 2018

The study examines the research trends of doctoral dissertations in Library Science and Information Science published in the U.S. for the last 5 years. Data collected from PQDT Global includes 1,016 doctoral dissertations containing "Library Science" or "Information Science" as subject headings, and keywords extracted from those dissertations were used for a network analysis, which helps identifying the intellectual structure of the dissertations. Also, the analysis using 103 subject heading keywords resulted in various centrality measures, including triangle betweenness centrality and nearest neighbor centrality, as well as 26 clusters of associated subject headings. The most frequently studied subjects include computer-related subjects, education-related subjects, and communication-related subjects, and a cluster with information science as the most central subject contains most of the computer-related keywords, while a cluster with library science as the most central subject contains many of the education-related keywords. Other related subjects include various user groups for user studies, and subjects related to information systems such as management, economics, geography, and biomedical engineering.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1496-1506
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• 2007

The environment of web service has changed a great deal due to the progress of internet technology and positive participation of users. The established web service is static and passive, but the recent web service is becoming dynamic and active. Web 2.0 reflects current web service change well. The primary feature of web 2.0 is positive participation of users. Since the size of generated information is becoming larger, it is highly required to share the information fast and correctly. The technology to satisfy this need is web syndication and tagging in web 2.0. The web syndication makes feeds for another site or users to receive the content of web site. In addition, the tagging is the kernel of a information. Many internet users share rapidly the information through tag search. In this paper, we propose the efficient technique to improve the web 2.0 technology such as web syndication and tagging by using the data collection engine. Data collection engine has stored in a database, a user's Web site to use the information. and it has a user's Web site with access to updated data to collect. The experimental results show that our approach can improve the search speed up to 3.14 times better than the existing method and reduce the size of data up to 66% for building associated tags.

• Economic and Environmental Geology
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• v.48 no.1
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• pp.89-101
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• 2015

The sour gas is natural gas containing components such as hydrogen sulphide and carbon dioxide that form acids when mixed with water. Element sulfur precipitates from sour gas when reservoir pressure and temperature decrease. According to the International Energy Agency, about 43% of the world's natural gas reserves(2,580 tcf or 73.057 tcm), excluding North America, are sour. The sour gas is often derived from the Germanic word 'sauer or acidic' and the etymology referred to as 'sour'. Sour gas requires special handling and infrastructure because it contains significant amounts of hydrogen sulphide, making it highly corrosive, flammable and explosive, and there fore more costly and dangerous to process. So the business of sour gas is affected by two important factors: the economic value of the gas, and the methods used in its production. According to be analyzed in the academic literature to sour gas(2000~2014) by the program of 'web of science', the research activities 145 papers in sour gas.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.57-64
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• 2017

Short message service (SMS) is one of the most important communication methods for people who use mobile phones. However, illegal advertising spam messages exploit people because they can be used without the need for friend registration. Recently, spam message filtering systems that use machine learning have been developed, but they have some disadvantages such as requiring many calculations. In this paper, we implemented a spam message filtering system using the set-based POI search algorithm and sentence similarity without servers. This algorithm can judge whether the input query is a spam message or not using only letter composition without any server computing. Therefore, we can filter the spam message although the input text message has been intentionally modified. We added a specific preprocessing option which aims to enable spam filtering. Based on the experimental results, we observe that our spam message filtering system shows better performance than the original set-based POI search algorithm. We evaluate the proposed system through extensive simulation. According to the simulation results, the proposed system can filter the text message and show high accuracy performance against the text message which cannot be filtered by the 3 major telecom companies.

• Journal of Korean Library and Information Science Society
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• v.51 no.1
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• pp.179-200
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• 2020

This study aims to detect the knowledge structure of Korean studies using document co-citation analysis and text mining techniques. This study divided Korean corpus into two perspectives: Self-perceived and others' perceived Korean studies. To this end, we collected 10,929 humanities and social literature containing the word Korea or Korean as a keyword in the SCOPUS database. As a result of analysis, a total of 20 subdomains were found in the knowledge structure of self-perception, and a total of 14 subdomains were found in the knowledge structure of otherts' perception. Differences in Korean Studies between two are: First, the sub-area of self-perceived Korean studies is subdivided into more diverse areas than the sub-area of other-perceived Korean studies. Second the major areas in self-perceived Korean studies are customers and services, industrialization, multiculturalism, mental health, tourism, Korean language, environment, and cities. Others' perceptions of Korean Studies are grouped into domestic and foreign situations of Korea, Korean pop culture, Koreans as US immigrants, and Korean language. Finally, the common areas of self-perception and others' perception were mental health, tourism, Korean language, North-Korean defectors, and juvenile delinquency.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.69-76
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• 2016

With the recent increase of the interest in IoT in almost all areas of industry, computing technologies have been increasingly applied in human environments such as houses, buildings, cars, and streets; in these IoT environments, speech recognition is being widely accepted as a means of HCI. The existing server-based speech recognition techniques are typically fast and show quite high recognition rates; however, an internet connection is necessary, and complicated server computing is required because a voice is recognized by units of words that are stored in server databases. This paper, as a successive research results of speech recognition algorithms for the Korean phonemic vowel 'ㅏ', 'ㅓ', suggests an implementation of speech recognition algorithms for the Korean phonemic vowel 'ㅣ'. We observed that almost all of the vocal waveform patterns for 'ㅣ' are unique and different when compared with the patterns of the 'ㅏ' and 'ㅓ' waveforms. In this paper we propose specific waveform patterns for the Korean vowel 'ㅣ' and the corresponding recognition algorithms. We also presents experiment results showing that, by adding neural-network learning to our algorithm, the voice recognition success rate for the vowel 'ㅣ' can be increased. As a result we observed that 90% or more of the vocal expressions of the vowel 'ㅣ' can be successfully recognized when our algorithms are used.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.167-176
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• 2005

This paper describes how the state tying model based on the decision tree which is one of Acoustic models used for speech recognition optimizes the model by reducing the number of mixture Gaussians of the output probability distribution. The state tying modeling uses a finite set of questions which is possible to include the phonological knowledge and the likelihood based decision criteria. And the recognition rate can be improved by increasing the number of mixture Gaussians of the output probability distribution. In this paper, we'll reduce the number of mixture Gaussians at the highest point of recognition rate by clustering the Gaussians. Bhattacharyya and Euclidean method will be used for the distance measure needed when clustering. And after calculating the mean and variance between the pair of lowest distance, the new Gaussians are created. The parameters for the new Gaussians are derived from the parameters of the Gaussians from which it is born. Experiments have been performed using the STOCKNAME (1,680) databases. And the test results show that the proposed method using Bhattacharyya distance measure maintains their recognition rate at $97.2\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. And the method using Euclidean distance measure shows that it maintains the recognition rate at $96.9\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. Then the methods can optimize the state tying model.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.348-355
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• 2010

In spite of development in speech recognition technology, speech recognition under noisy environment is still a difficult task. To solve this problem, Researchers has been proposed different methods where they have been used visual information except audio information for visual speech recognition. However, visual information also has visual noises as well as the noises of audio information, and this visual noises cause degradation in visual speech recognition. Therefore, it is one the field of interest how to extract visual features parameter for enhancing visual speech recognition performance. In this paper, we propose a method for visual feature parameter extraction based on image-base approach for enhancing recognition performance of the HMM based visual speech recognizer. For experiments, we have constructed Audio-visual database which is consisted with 105 speackers and each speaker has uttered 62 words. We have applied histogram matching, lip folding, RASTA filtering, Liner Mask, DCT and PCA. The experimental results show that the recognition performance of our proposed method enhanced at about 21% than the baseline method.