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" Big data analysis and deep learning applications : "
Thi Thi Zin, Jerry Chun-Wei Lin, editors.
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BL
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| Record Number
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889744
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| Main Entry
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International Conference on Big Data Analysis and Deep Learning(1st :2018 :, Miyazaki-shi, Japan)
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| Title & Author
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Big data analysis and deep learning applications : : proceedings of the first International Conference on Big Data Analysis and Deep Learning /\ Thi Thi Zin, Jerry Chun-Wei Lin, editors.
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| Publication Statement
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Singapore :: Springer,, [2018]
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, ©2019
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| Series Statement
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Advances in intelligent systems and computing ;; volume 744
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| Page. NO
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1 online resource
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| ISBN
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9789811308697
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: 9811308691
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9789811308680
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Intro; Preface; Organizing Committee; General Chair; General Co-chairs; Advisory Committee Chairs; Program Committee Chair; Program Committee Co-chair; Publication Chairs; Invited Session Chairs; International Technical Program Committee Members; Contents; Big Data Analysis; Data-Driven Constrained Evolutionary Scheme for Predicting Price of Individual Stock in Dynamic Mark ... ; Abstract; 1 Introduction; 1.1 Artificial Neural Network; 1.2 Genetic Algorithms (GA); 2 Problem Scenario and Assumptions; 2.1 Shift Detection (Trigger); 2.2 Shift Direction; 2.3 Shift Degree; 3 Methodology
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3.1 Shift Detection Function3.2 Shift Direction and Shift Degree; 3.3 Fine Tuning; 4 Discussion; References; Predictive Big Data Analytics Using Multiple Linear Regression Model; Abstract; 1 Introduction; 2 Regression Analysis and Big Data; 3 Multiple Linear Regression; 3.1 MapReduce Framework; 4 The Proposed MapReduce Based Multiple Linear Regression Model with QR Decomposition; 4.1 Implementation of the Proposed Model; 5 Experimentation, Discussion and Conclusion; 5.1 Experimental Setup; 5.2 Discussion and Conclusion; References
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4 Applications5 Conclusion; References; Real Time Semantic Events Detection from Social Media Stream; Abstract; 1 Introduction; 2 Related Works; 3 Semantic Events Detection; 4 Semantic Words Extraction; 4.1 Data Preprocessing; 5 Real Time Burst Detection; 6 Semantic Events Detection; 7 Experimental Results; 8 Conclusion; References; Community and Outliers Detection in Social Network; Abstract; 1 Introduction; 2 Related Work; 3 Background Theory; 3.1 Graph; 3.2 Node Degree and Its Neighborhood; 3.3 Communities; 3.4 Vertex Centrality; 3.5 Outliers; 3.6 Vertex Similarity; 4 Proposed Approach
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5.3 Internet of Things (IoT)6 Data Analysis; 6.1 Preprocessing Text Data; 6.2 Feature Extraction: (tf-idf); 6.3 Maximum Entropy Classifier (MaxEnt); 6.4 Classifier Trainer Algorithms; 7 Experimental Results; 8 Conclusion and Future Work; References; A Survey on Influence and Information Diffusion in Twitter Using Big Data Analytics; Abstract; 1 Introduction; 2 Twitter Network; 2.1 Twitter Metrics; 2.2 Twitter API; 2.3 Data Collection; 3 Influence Models in Social Networks; 3.1 Definition of Influence; 3.2 Information Diffusion in Twitter; 3.3 User Influence Models in Literature
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Evaluation for Teacher's Ability and Forecasting Student's Career Based on Big DataAbstract; 1 Introduction; 2 Related Work; 3 Processing; 3.1 Data Collection; 4 Implementation; 4.1 Analyzing the Teacher's Ability; 4.2 Forecasting the Student's Career; 5 Expected Result; 6 Conclusion; References; Tweets Sentiment Analysis for Healthcare on Big Data Processing and IoT Architecture Using Maximum Entropy Classifier; Abstract; 1 Introduction; 2 Related Work; 3 Overall System Architecture; 4 Data Collection; 5 Data Store and Processing; 5.1 Hadoop; 5.2 Raspberry Pi Hadoop Cluster
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| Abstract
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This book presents a compilation of selected papers from the first International Conference on Big Data Analysis and Deep Learning Applications (ICBDL 2018), and focuses on novel techniques in the fields of big data analysis, machine learning, system monitoring, image processing, conventional neural networks, communication, industrial information, and their applications. Readers will find insights to help them realize more efficient algorithms and systems used in real-life applications and contexts, making the book an essential reference guide for academic researchers, professionals, software engineers in the industry, and regulators of aviation authorities. .
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| Subject
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Big data, Congresses.
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Data mining, Congresses.
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Machine learning, Congresses.
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Big data.
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COMPUTERS-- Data Processing-- General.
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Data mining.
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Machine learning.
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| Dewey Classification
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005
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| LC Classification
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QA76.9.B45
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| Added Entry
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Lin, Jerry Chun-Wei
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Zin, Thi Thi
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