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Identifying Mobile Owner based on Authorship Attribution using WhatsApp Conversation

  • Almezaini, Badr Mohammd;Khan, Muhammad Asif
    • International Journal of Computer Science & Network Security
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    • v.21 no.7
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    • pp.317-323
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    • 2021
  • Social media is increasingly becoming a part of our daily life for communicating each other. There are various tools and applications for communication and therefore, identity theft is a common issue among users of such application. A new style of identity theft occurs when cybercriminals break into WhatsApp account, pretend as real friends and demand money or blackmail emotionally. In order to prevent from such issues, data mining can be used for text classification (TC) in analysis authorship attribution (AA) to recognize original sender of the message. Arabic is one of the most spoken languages around the world with different variants. In this research, we built a machine learning model for mining and analyzing the Arabic messages to identify the author of the messages in Saudi dialect. Many points would be addressed regarding authorship attribution mining and analysis: collect Arabic messages in the Saudi dialect, filtration of the messages' tokens. The classification would use a cross-validation technique and different machine-learning algorithms (Naïve Baye, Support Vector Machine). Results of average accuracy for Naïve Baye and Support Vector Machine have been presented and suggestions for future work have been presented.

Mobile Web-based Education: Engagement and Satisfaction with HiChart among Pregnant Women

  • Kim, Hyo Jin;Kang, Hee Sun
    • Child Health Nursing Research
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    • v.25 no.3
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    • pp.303-311
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    • 2019
  • Purpose: This study aimed to examine engagement and satisfaction with a mobile web-based education program (HiChart) among pregnant women. Methods: A cross-sectional descriptive study was conducted of 97 pregnant women hospitalized for obstetric care. Data were collected from October 1 to November 30, 2016, and were analyzed with descriptive statistics. Results: Among participants, 16.5% engaged fully with HiChart, while 43.3% engaged partially. The overall satisfaction with HiChart was high. Some main reasons for not engaging with the education were participants' unawareness of the text messages, lack of time, and poor internet connection. The participants suggested that more educational content needed to be covered, such as coping with infant emergencies and information about the neonatal intensive care unit. Conclusion: To increase pregnant women's engagement with mobile web-based education, efforts are needed to strengthen the system of sending text messages as part of mobile web-based education to all patients, to inform pregnant women that an educational web link was sent, and to encourage them to engage with mobile web-based education. Furthermore, it is essential to improve the HiChart service by providing educational content corresponding to users' needs.

The Strategy of Wireless Power Transfer for Light Rail Transit By Core Technologies Analysis Based on Text Mining

  • Meng, Xiang-Yu;Han, Young-Jae;Eum, Soo-Min;Cho, Sung-Won
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.11
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    • pp.193-201
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    • 2018
  • In this paper, we extracted relevant patent data and conducted statistical analysis to understand the technical development trend related to Wireless Power Transfer (WPT) for Light Rail Transit (LRT). Recently, with the development of WPT technologies, the Light Rail Transit (LRT) industry is concentrating on applying WPT to the power supply system of trains because of their advantages compared wired counterpart, such as low maintenance cost and high stability. This technology is divided into three areas: wireless feeding and collecting technology, high-frequency power converter technology and orbital and infrastructure technology. From each specific area, key words in patent document were extracted by TF-IDF method and analyzed by social network. In the keyword network, core word of each specific technology were extracted according to their degree centrality. Then, the multi-word phrases were also built to represent the concept of core technologies. Finally, based on the analysis results, the development strategies for each specifics technical area of WPT in LRT filed will be provided.

A Study on City Brand Evaluation Method Using Text Mining : Focused on News Media (텍스트 마이닝 기법을 활용한 도시 브랜드 평가방법론 연구 : 뉴스미디어를 중심으로)

  • Yoon, Seungsik;Shin, Minchul;Kang, Juyoung
    • Journal of Information Technology Services
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    • v.18 no.1
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    • pp.153-171
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    • 2019
  • Competition among cities has become fierce with decentralization and globalization, and each city tries to establish a brand image of the city to build its competitiveness and implement its policies based on it. At this time, surveys, expert interviews, etc. are commonly used to establish city brands. These methods are difficult to establish as sampling methods an empirical component, the biggest component of a city brand. In this paper, therefore, based on the precedent research's urban brand measurement and components, the words representing each city image property were extracted and relocated to five indicators to form the evaluation index. The constructed indicators have been validated through the review of three experts. Through the index, we analyzed the brands of four cities, Ulsan, Incheon, Yeosu, and Gyeongju, and identified the factors by using Topic Modeling and Word Cloud. This methodology is expected to reduce costs and monitor timely in identifying and analyzing urban brand images in the future.

Analysis of domestic and foreign research trends of Tricholoma matsutake using text mining techniques

  • Choi, Ah Hyeon;Kang, Jun Won
    • Korean Journal of Agricultural Science
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    • v.48 no.3
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    • pp.505-514
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    • 2021
  • Among non-timber forest products, Tricholoma matsutake is a high value added item. Many countries, including Korea, China, and Japan, are doing research and technology development to increase artificial cultivation and productivity. However, the production of T. matsutake is on the decline due to global warming, abnormal temperatures and pine tree pest problems. Therefore, it is necessary to identify trends in domestic and foreign research on T. matsutake, respond to preemptive research and development to preserve the genetic resources of T. matsutake and increase its productivity. Based on the correlation between keywords in the high frequency keywords, it was observed that microbial clusters of T. matsutake are mainly found in Korea. The main focus in China has been the pharmacology studies on the ingredients of T. matsutake. The main focus in Japan has been on preserving the genetic diversity and species of T. matsutake. Thus, future domestic studies of T. matsutake will require pharmacological studies on the ingredients of T. matsutake and on its genetic diversity and species conservation. In addition, unlike China and Japan, genetic keywords did not appear in Korea at high frequency. Therefore, Korea will have to proceed with research using modern molecular biology techniques.

Non-Newtonian Intrinsic Viscosities of Biopolymeric and Nonbiopolymeric Solutions (I)

  • Jang, Chun-Hag;Kim, Jong-Ryul;Ree, Tai-Kyue
    • Bulletin of the Korean Chemical Society
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    • v.8 no.4
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    • pp.318-324
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    • 1987
  • Experimental results for viscous flow of poly (${\gamma}$ -methyl L-glutamate) solutions have been published elsewhere. The data of $[{\eta}]^f / [{\eta}]^0$ are expressed by the following equation, $\frac{[{\eta}^f]}{[{\eta}^{\circ}]}=1-\frac{A}{\eta^\circ}{1-\frac{sin^{-1}[{\beta}_2(f/{\eta}_0)\;{e}xp\;(-c_2f^2/{\eta}_0^2kT)]}{{\beta}_2f/{\eta}_0}$ (A1) where $[{\eta}]^f\; and\; [{\eta} ]^0$ are the intrinsic viscosity at shear stress f and zero, respectively, $ A{\equiv}lim\limits_{C{\rightarrow}0}[(1/C)(X_2/{\alpha}_2)({\beta}_2/{\eta}_0)],{\eta}_0$ viscosity of the solvent, ${\beta}_2$ is the relaxation time of flow unit 2, $c_2$ is a constant related to the elasticity of flow unit 2. The theoretical derivation of Eq.(A1) is given in the text. The experimental curves of $[{\eta}]^f / [{\eta}]^0$ vs. log f are compared with the theoretical curves calculated from Eq.(A1) with good results. Eq.(A1) is also applied to non-biopolymeric solutions, and it was found that in the latter case $c_2 = 0.$ The reason for this is explained in the text. The problems related to non-Newtonian flows are discussed.

Automatic Generation Subtitle Service with Kinetic Typography according to Music Sentimental Analysis (음악 감정 분석을 통한 키네틱 타이포그래피 자막 자동 생성 서비스)

  • Ji, Youngseo;Lee, Haram;Lim, SoonBum
    • Journal of Korea Multimedia Society
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    • v.24 no.8
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    • pp.1184-1191
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    • 2021
  • In a pop song, the creator's intention is communicated to the user through music and lyrics. Lyric meaning is as important as music, but in most cases lyrics are delivered to users in a static form without non-verbal cues. Providing lyrics in a static text format is inefficient in conveying the emotions of a music. Recently, lyrics video with kinetic typography are increasingly provided, but producing them requires expertise and a lot of time. Therefore, in this system, the emotions of the lyrics are found through the analysis of the text of the lyrics, and the deep learning model is trained with the data obtained by converting the melody into a Mel-spectrogram format to find the appropriate emotions for the music. It sets properties such as motion, font, and color using the emotions found in the music, and automatically creates a kinetic typography video. In this study, we tried to enhance the effect of conveying the meaning of music through this system.

Analysis of Media Articles on COVID-19 and Nurses Using Text Mining and Topic Modeling (텍스트 마이닝과 토픽모델링 분석을 활용한 코로나19와 간호사에 대한 언론기사 분석)

  • An, Jiyeon;Yi, Yunjeong;Lee, Bokim
    • Research in Community and Public Health Nursing
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    • v.32 no.4
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    • pp.467-476
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    • 2021
  • Purpose: The purpose of this study is to understand the social perceptions of nurses in the context of the COVID-19 outbreak through analysis of media articles. Methods: Among the media articles reported from January 1st to September 30th, 2020, those containing the keywords '[corona or Wuhan pneumonia or covid] and [nurse or nursing]' are extracted. After the selection process, the text mining and topic modeling are performed on 454 media articles using textom version 4.5. Results: Frequency Top 30 keywords include 'Nurse', 'Corona', 'Isolation', 'Support', 'Shortage', 'Protective Clothing', and so on. Keywords that ranked high in Term Frequency-Inverse Document Frequency (TF-IDF) values are 'Daegu', 'President', 'Gwangju', 'manpower', and so on. As a result of the topic analysis, 10 topics are derived, such as 'Local infection', 'Dispatch of personnel', 'Message for thanks', and 'Delivery of one's heart'. Conclusion: Nurses are both the contributors and victims of COVID-19 prevention. The government and the nurses' community should make efforts to improve poor working conditions and manpower shortages.

Research on Satisfaction Evaluation Based on Tourist Big Data

  • Guo, Hanwen;Liu, Ziyang;Jiao, Zeyu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.1
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    • pp.231-244
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    • 2022
  • With the improvement of people's living standards and the development of tourism, tourists have greater freedom in choosing destinations. Therefore, as an indicator of satisfaction with scenic spots, tourist comments are becoming increasingly prominent. This paper aims to compare and analyze the landscape image of the Five Great Mountains in China and provide specific strategies for its development. The online reviews of tourists on the Online Travel Agency (OTA) website about the Five Great Mountains from 2015 to 2018 are collected as research samples. The text analysis method and R language are used to analyze the content of the tourist reviews, while the high-frequency words in the word cloud are used for visual display. In addition, the entropy weight method is used to determine the index weight and tourist satisfaction is evaluated to understand the weaknesses of those scenic spots. The results of the study show that firstly, the tourist satisfaction with the Five Great Mountains is basically consistent with its popularity. Secondly, through weight analysis, tourists pay special attention to the landscape features and environmental health of the scenic area, so that relevant departments should focus on building the landscape characteristics and improving the environmental health of the scenic area. At the same time, the accommodation and service management of the scenic spot cannot be ignored. Finally, according to the analysis results, suggestions are made on how to improve the tourist satisfaction with the Five Great Mountains.

A Comparative Study of Dietary Related Zero-waste Patterns and Consumer Responses Before and After COVID-19 (코로나-19 이전과 이후 식생활 관련 제로웨이스트 운동 양상과 소비자 반응 비교)

  • Park, In-Hyoung;Park, You-min;Lee, Cheol;Sun, Jung-eun;Hu, Wendie;Chung, Jae-Eun
    • Human Ecology Research
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    • v.60 no.1
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    • pp.21-38
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    • 2022
  • This study uses text mining compares and contrasts consumers' social media discourses on dietary related zero-waste movement before and after COVID-19. The results indicate that the amount of buzz on social networks for the zero- waste movement has been increasing after COVID-19. Additionally, the results of frequency analysis and topic modeling revealed that subjects associated with zero-waste movement were more diversified after COVID-19. Although the results of a sentiment analysis and word cloud visualization confirmed that consumers' positive responses toward the zero-waste have been increasing, they also revealed a need to educate and encourage those who are still not aware of the need for zero-waste. Finally, consumers mentioned only a small number of companies participating in zero-waste movement on SNS, indicating that the level of active involvement by such companies is much lower than that of consumers. Theoretical and educational implications as well as those for government policy-making are considered.