• Language and Information
• /
• v.10 no.1
• /
• pp.47-69
• /
• 2006

Recently, there has been a surge of interests concerning the construction and utilization of a Korean thesaurus. In this paper, a semi-automatic method for generating a lexical-semantic network of Korean '-ha' verbs is presented through an analysis of the lexical definitions of these verbs. Initially, through the use of several tools that can filter out and coordinate lexical data, pairs constituting a word and a definition were prepared for treatment in a subsequent step. While inspecting the various definitions of each verb, we extracted and coordinated the head words from the sentences that constitute the definition of each word. These words are thought to be the main conceptual words that represent the sense of the current verb. Using these head words and related information, this paper shows that the creation of a thesaurus could be achieved without any difficulty in a semi-automatic fashion.

• Journal of the Korea Society of Computer and Information
• /
• v.24 no.7
• /
• pp.125-133
• /
• 2019

Because military weapons systems for special purposes are small and complex, they are not easy to maintain. Therefore, it is very important to maintain combat strength through quick maintenance in the event of a breakdown. In particular, naval ships are complex weapon systems equipped with various equipment, so other equipment must be considered for maintenance in the event of equipment failure, so that skilled maintenance personnel have a great influence on rapid maintenance. Therefore, in this paper, we analyzed maintenance data of defense equipment maintenance information system through text mining and social network analysis(SNA), and tried to identify the naval ship maintenance expertise. The defense equipment maintenance information system is a system that manages military equipment efficiently. In this study, the data(2,538cases) of some naval ship maintenance teams were analyzed. In detail, we examined the contents of main maintenance and maintenance personnel through text mining(word cloud, word network). Next, social network analysis(collaboration analysis, centrality analysis) was used to confirm the collaboration relationship between maintenance personnel and maintenance expertise. Finally, we compare the results of text mining and social network analysis(SNA) to find out appropriate methods for finding and finding naval ship maintenance expertise.

• International Journal of Advanced Culture Technology
• /
• v.5 no.4
• /
• pp.57-62
• /
• 2017

In this paper, we applied long short term memory(LSTM) for classifying political polarity in cyber public sphere. The data collected from the cyber public sphere is transformed into word corpus data through word embedding. Based on this word corpus data, we train recurrent neural network (RNN) which is connected by LSTM's. Softmax function is applied at the output of the RNN. We conducted our proposed system to obtain experimental results, and we will enhance our proposed system by refining LSTM in our system.

• Journal of Information Technology Services
• /
• v.11 no.3
• /
• pp.227-240
• /
• 2012

Given the prevalence of internet and web 2.0, SNS(Social Network Service) market is growing rapidly. IT providers which focused marketing point on network hub have become to disseminate SNS mainly now. Many users are using the various functions of SNS to communicate each other or share the information. At this point, identifying the influencing factors to WOM(Word-Of-Mouth) of SNS is very important. In this paper, we aim to examine the effects of perceived variables on the WOM of SNS. In order to analyze the antecedents, we selected perceived factors such as perceived usefulness, perceived easiness, perceived enjoyment and perceived crowd. For statistical analysis, we surveyed real users of SNS. As a result, all antecedents of WOM showed significant influence and among the variables the perceived enjoyment has top standardized coefficient. In addition, perceived crowd has significant on perceived easiness, perceived enjoyment but not on perceived usefulness. The result of this research can be useful guidelines to increase SNS Market.

• The Journal of Information Systems
• /
• v.24 no.1
• /
• pp.1-25
• /
• 2015

Social Network Service (SNS) has been played an important role in the life with the expansion of the modern technology in the cellular communication. More knowledge and understanding should be inevitable even if companies have taken advantage of SNS through word of mouth as one of the new paradigm. In most cases the crucial benefit or peculiarity of SNS has been overlooked because only general aspects of SNS have been applied in the online situation. As a result of this, same paradigm has been considered in reality as SNS was just used one of the marketing tools. However, essential aspects of SNS were investigated to see the relation of usage intention and word of mouth in this study. The hypothesis of the effect of continuous intention of the usage, trust and word of mouth was made and reviewed statistically. The statistical analysis showed there was significant among relationship, context, perceived service quality and continuous intention of the usage. In addition to that, self-expression, relationship, perceived service quality and trust were significant. Finally the continuous intention of the usage and word of mouth was significant as well. Based on this study, SNS provided by the companies could be effective to the customers in terms of word of mouth while different trend was shown in terms of trust.

• International Journal of Advanced Culture Technology
• /
• v.10 no.4
• /
• pp.361-368
• /
• 2022

This study seeks to determine the research trend of late adolescents by utilizing big data. Also, seek for research trends related to activity participation, treatment, and mediation to provide academic implications. For this process, gathered 1.000 academic papers and used TF-IDF analysis method, and the topic modeling based on co-occurrence word network analysis method LDA (Latent Dirichlet Allocation) to analyze. In conclusion this study conducted analysis of activity participation, treatment, and mediation of late adolescents by TF-IDF analysis method, co-occurrence word network analysis method, and topic modeling analysis based on LDA(Latent Dirichlet Allocation). The results were proposed through visualization, and carries significance as this study analyzed activity, treatment, mediation factors of late adolescents, and provides new analysis methods to figure out the basic materials of activity participation trends, treatment, and mediation of late adolescents.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.103-104
• /
• 2018

Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2018.05a
• /
• pp.424-425
• /
• 2018

Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.484-485
• /
• 2019

Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.565-566
• /
• 2021

Recently, interest in data analysis has increased as the importance of big data becomes more important. Particularly, as social media data and academic research communities become more active and important, analysis becomes more important. In this study, co-word analysis was conducted through altmetrics articles collected from 2012 to 2017. In this way, the co-occurrence network map is derived from the keyword and the emphasized keyword is extracted.