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001454564 001__ 1454564
001454564 003__ OCoLC
001454564 005__ 20230314003218.0
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001454564 008__ 230211s2023\\\\sz\\\\\\o\\\\\101\0\eng\d
001454564 019__ $$a1369616155
001454564 020__ $$a9783031196089$$q(electronic bk.)
001454564 020__ $$a3031196082$$q(electronic bk.)
001454564 020__ $$z3031196074
001454564 020__ $$z9783031196072
001454564 0247_ $$a10.1007/978-3-031-19608-9$$2doi
001454564 035__ $$aSP(OCoLC)1369660050
001454564 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX$$dEBLCP
001454564 049__ $$aISEA
001454564 050_4 $$aQA76.9.B45
001454564 08204 $$a005.7$$223/eng/20230214
001454564 1112_ $$aIEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering$$n(7th :$$d2022 :$$cĐà Nẵng, Vietnam)
001454564 24510 $$aBig data, cloud computing, and data science engineering /$$cRoger Lee, editor.
001454564 260__ $$aCham :$$bSpringer,$$c2023.
001454564 300__ $$a1 online resource (190 p.).
001454564 4901_ $$aStudies in Computational Intelligence ;$$vv.1075
001454564 500__ $$aSecurity Policy Deploying System for Zero Trust Environment
001454564 500__ $$aIncludes index.
001454564 5050_ $$aIntro -- Foreword -- Contents -- Contributors -- Research on Development of Sponsorship Effect Analysis Module Using Text Mining Technique -- 1 Introduction -- 2 Theoretical Background -- 2.1 Definition of Sponsorship and Sponsorship Effect -- 2.2 Study of Text Analysis Techniques -- 2.3 Prior Studies Using News Text Analysis -- 3 Research Method and Result -- 3.1 Research and Development Process -- 3.2 Data Collection -- 3.3 Development of Sponsor Effectiveness Analysis Module -- 3.4 Building a Simple Dashboard -- 4 Conclusions -- References
001454564 5058_ $$aA Study on the Relationship Between ESG News Keywords and ESG Ratings -- 1 Introduction -- 2 Theoretical Background -- 2.1 Overview of ESG -- 2.2 Related Works -- 3 Research Method -- 3.1 Data Collection -- 4 Data Analysis -- 4.1 Frequency Analysis and Word Cloud -- 4.2 Relationship Analysis of the Influence on ESG Rating -- 5 Conclusion -- References -- Development of Associated Company Network Visualization Techniques Using Company Product and Service Information-Using Cosine Similarity Function -- 1 Introduction -- 2 Theoretical Background and Prior Research -- 2.1 Text Mining Research
001454564 5058_ $$a2.2 Social Network Analysis Study -- 2.3 Associated Companies Analysis -- 3 Research Method -- 4 Analysis Results -- 5 Conclusion -- References -- Hybrid CNN-LSTM Based Time Series Data Prediction Model Study -- 1 Introduction -- 2 Theoretical Background -- 2.1 Time-Series Analysis -- 2.2 Recurrent Neural Network -- 2.3 Long- Short-Term Memory -- 2.4 Convolutional Neural Network -- 3 Research Method -- 3.1 Methodology to Predict Time-Series Using CNN-LSTM -- 3.2 Performance Procedure -- 4 Experiments and Results -- 4.1 Evaluation Methods -- 4.2 Evaluation Methods
001454564 5058_ $$a4.3 Comparative Evaluation of Deep Learning Models -- 5 Conclusion -- References -- A Study on Predicting Employee Attrition Using Machine Learning -- 1 Introduction -- 2 Theoretical Background -- 2.1 Data Analytics in the Human Resources (HR) -- 2.2 Machine Learning Algorithm -- 3 Research Design -- 3.1 Research Framework -- 3.2 Feature Selection Using Filter Method -- 3.3 Classification Prediction Model -- 3.4 Machine Learning Performance Measurement -- 4 Research Result -- 4.1 Data Set -- 4.2 Data Preprocessing -- 4.3 Feature Selection -- 4.4 Ensemble Prediction Model Performance
001454564 5058_ $$a5 Conclusion -- References -- A Study on the Intention to Continue Using a Highway Driving Assistance (HDA) System Based on Advanced Driver Assistance System (ADAS) -- 1 Introduction -- 2 Theoretical Background -- 2.1 Advanced Driver Assistance Systems (ADAS) -- 2.2 Highway Driving Assistance System (HDA) -- 2.3 HDA (Highway Driving Assist) User Characteristics -- 2.4 Protection Motivation Theory (PMT) -- 2.5 Technology Acceptance Model (TAM) -- 3 Research Method -- 3.1 Data Collection -- 3.2 Research Model and Selection of Variables -- 4 Data Result Analysis -- 5 Conclusions -- References
001454564 506__ $$aAccess limited to authorized users.
001454564 520__ $$aThis book presents scientific results of the 7th IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2021) which was held on August 4-6, 2022 in Danang, Vietnam. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. All aspects (theory, applications, and tools) of computer and information science, the practical challenges encountered along the way, and the solutions adopted to solve them are all explored here in the results of the articles featured in this book. The conference organizers selected the best papers from those papers accepted for presentation at the conference. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 15 of the conferences most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.
001454564 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed February 14, 2023).
001454564 650_0 $$aBig data$$vCongresses.
001454564 650_0 $$aCloud computing$$vCongresses.
001454564 650_0 $$aSoftware engineering$$vCongresses.
001454564 655_0 $$aElectronic books.
001454564 7001_ $$aLee, Roger$$q(Roger Chin Tat),$$eeditor.
001454564 77608 $$iPrint version:$$aLee, Roger$$tBig Data, Cloud Computing, and Data Science Engineering$$dCham : Springer International Publishing AG,c2023$$z9783031196072
001454564 830_0 $$aStudies in computational intelligence ;$$vv. 1075.
001454564 852__ $$bebk
001454564 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-19608-9$$zOnline Access$$91397441.1
001454564 909CO $$ooai:library.usi.edu:1454564$$pGLOBAL_SET
001454564 980__ $$aBIB
001454564 980__ $$aEBOOK
001454564 982__ $$aEbook
001454564 983__ $$aOnline
001454564 994__ $$a92$$bISE