This book covers topics like big data analyses, services, and smart data. It contains (i) invited papers, (ii) selected papers from the Sixth International Conference on Big Data Applications and Services (BigDAS 2018), as well as (iii) extended papers from the Sixth IEEE International Conference on Big Data and Smart Computing (IEEE BigComp 2019). The aim of BigDAS is to present innovative results, encourage academic and industrial interaction, and promote collaborative research in the field of big data worldwide. BigDAS 2018 was held in Zhengzhou, China, on August 19-22, 2018, and organized…mehr
This book covers topics like big data analyses, services, and smart data. It contains (i) invited papers, (ii) selected papers from the Sixth International Conference on Big Data Applications and Services (BigDAS 2018), as well as (iii) extended papers from the Sixth IEEE International Conference on Big Data and Smart Computing (IEEE BigComp 2019). The aim of BigDAS is to present innovative results, encourage academic and industrial interaction, and promote collaborative research in the field of big data worldwide. BigDAS 2018 was held in Zhengzhou, China, on August 19-22, 2018, and organized by the Korea Big Data Service Society and TusStar. The goal of IEEE BigComp, initiated by Korean Institute of Information Scientists and Engineers (KIISE), is to provide an international forum for exchanging ideas and information on current studies, challenges, research results, system developments, and practical experiences in the emerging fields of big data and smart computing. IEEE BigComp 2019was held in Kyoto, Japan, on February 27-March 02, 2019, and co-sponsored by IEEE and KIISE.
Prof. Wookey Lee. He received his B.S., M.S., and Ph.D. degrees from Seoul National University, South Korea, and his M.S.E. degree from Carnegie Mellon University, USA. Currently, he is the director of VOICE AI institute and a professor at Inha University, South Korea, and has been a visiting professor in Dept. of Computer Science, University of British Columbia, Canada. He won the best paper awards in IEEE TCSC, KORMS, KOSIPER, and KIISE. He currently is the editor-in-chief of the Journal of Information Technology and Architecture, and Journal of Big Data Service, also an associate editor of World Wide Web Journal, Supercomputing, Cluster Computing, Sensors, etc. He has served as the president of Korea DataBase Society and an executive committee member of IEEE TCDE. He has participated as a steering committee of BigComp, and a PC member for APWeb, BigComp, CIKM, IEEE DEST, iiWAS, ITA, and WAIM, and an Organizing Committee member for DASFAA,EA, SRDS, and VLDB, etc. His research interests are Deep Learning, graph search, Voice-informatics, patent information, mobile and Data Warehousing, etc. Carson Leung is currently a Full Professor at the University of Manitoba, Canada. He obtained his B.Sc. (Hons.), M.Sc. and Ph.D. from the University of British Columbia, Canada. He has published more than 250 papers on the topics of databases, data mining, big data computing, social network analysis, as well as visual analytics-including papers in ACM Transactions on Database Systems (TODS), Social Network Analysis and Mining (SNAM), Future Generation Computer Systems (FGCS), Journal of Organizational Computing and Electronic Commerce (JOCEC), IEEE International Conference on Data Engineering (ICDE), IEEE International Conference on Data Mining (ICDM), and Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). Over the past few years, he has served on (i) the Steering Committee of IEEE SmartData 2020, (ii) the Advisory Committee of IEEE CBDCom 2019, (iii) the Organizing Committee of ACM SIGMOD 2008, IEEE/ACM ASONAM 2014, ACM CIKM 2018, IEEE BigComp 2020, IEEE DSAA 2020, and IEEE ICDM 2020. He has also served as (i) a General Chair of IEEE CBDCom 2016 and IEEE SmartData 2018, (ii) a Program Chair of IEEE CBDCom 2020 and IDEAS 2020, as well as (iii) a PC member of numerous international conferences including ACM KDD and ECML/PKDD. He is a senior member of both ACM and IEEE. Prof. Aziz Nasridinov is currently an Associate Professor of computer science with Chungbuk National University. He received the B.Sc. degree from the Tashkent University of Information Technologies in 2006 and the M.Sc. and Ph.D. degrees from Dongguk University in 2009 and 2012, respectively. Prof. Aziz Nasridinov has published over 20 papers in various high-ranked international journals and conferences. He has also served as a program committee member and co-organizer for numerous top-tier conferences, including ACM SAC, IEEE Big Data, and IEEE Globecom, and also served in the editorial board of several international journals. His research interests include traditional databases, big data analytics with machine learning, and distributed processing system applications.
Inhaltsangabe
Chapter 1. Analysis of the Effects of Nature and Facility Environmental Attributes on the Cause of Death from Disease.- Chapter 2. Big Data Computing and Mining in a Smart World.- Chapter 3. Data Science for Big Data Applications and Services: Data Lake Management, Data Analytics and Visualization.- Chapter 4. Detection of Editing Bursts and Extraction of Significant Keyphrases from Wikipedia Edit History.- Chapter 5. Emotion Detection on Twitter Textual Data.- Chapter 6. Factors Affecting an Organization's Information Security Performance: The Characteristics of Information Security Officers.- Chapter 7. Living Labs as the Methodology: Using for Verifying Certification Criteria of New Convergence Products.- Chapter 8. Vertical Data Mining from Relational Data and Its Application to COVID-19.
Chapter 1. Analysis of the Effects of Nature and Facility Environmental Attributes on the Cause of Death from Disease.- Chapter 2. Big Data Computing and Mining in a Smart World.- Chapter 3. Data Science for Big Data Applications and Services: Data Lake Management, Data Analytics and Visualization.- Chapter 4. Detection of Editing Bursts and Extraction of Significant Keyphrases from Wikipedia Edit History.- Chapter 5. Emotion Detection on Twitter Textual Data.- Chapter 6. Factors Affecting an Organization’s Information Security Performance: The Characteristics of Information Security Officers.- Chapter 7. Living Labs as the Methodology: Using for Verifying Certification Criteria of New Convergence Products.- Chapter 8. Vertical Data Mining from Relational Data and Its Application to COVID-19.
Chapter 1. Analysis of the Effects of Nature and Facility Environmental Attributes on the Cause of Death from Disease.- Chapter 2. Big Data Computing and Mining in a Smart World.- Chapter 3. Data Science for Big Data Applications and Services: Data Lake Management, Data Analytics and Visualization.- Chapter 4. Detection of Editing Bursts and Extraction of Significant Keyphrases from Wikipedia Edit History.- Chapter 5. Emotion Detection on Twitter Textual Data.- Chapter 6. Factors Affecting an Organization's Information Security Performance: The Characteristics of Information Security Officers.- Chapter 7. Living Labs as the Methodology: Using for Verifying Certification Criteria of New Convergence Products.- Chapter 8. Vertical Data Mining from Relational Data and Its Application to COVID-19.
Chapter 1. Analysis of the Effects of Nature and Facility Environmental Attributes on the Cause of Death from Disease.- Chapter 2. Big Data Computing and Mining in a Smart World.- Chapter 3. Data Science for Big Data Applications and Services: Data Lake Management, Data Analytics and Visualization.- Chapter 4. Detection of Editing Bursts and Extraction of Significant Keyphrases from Wikipedia Edit History.- Chapter 5. Emotion Detection on Twitter Textual Data.- Chapter 6. Factors Affecting an Organization’s Information Security Performance: The Characteristics of Information Security Officers.- Chapter 7. Living Labs as the Methodology: Using for Verifying Certification Criteria of New Convergence Products.- Chapter 8. Vertical Data Mining from Relational Data and Its Application to COVID-19.
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