Big Data: 7th CCF Conference, BigData 2019, Wuhan, China, September 26–28, 2019, Proceedings

Author:   Hai Jin ,  Xuemin Lin ,  Xueqi Cheng ,  Xuanhua Shi
Publisher:   Springer Verlag, Singapore
Edition:   1st ed. 2019
Volume:   1120
ISBN:  

9789811518980


Pages:   432
Publication Date:   28 November 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Big Data: 7th CCF Conference, BigData 2019, Wuhan, China, September 26–28, 2019, Proceedings


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Overview

This book constitutes the proceedings of the 7th CCF Conference on Big Data, BigData 2019, held in Wuhan, China, in October 2019. The 30 full papers presented in this volume were carefully reviewed and selected from 324 submissions. They were organized in topical sections as follows: big data modelling and methodology; big data support and architecture; big data processing; big data analysis; and big data application.

Full Product Details

Author:   Hai Jin ,  Xuemin Lin ,  Xueqi Cheng ,  Xuanhua Shi
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Verlag, Singapore
Edition:   1st ed. 2019
Volume:   1120
Weight:   0.682kg
ISBN:  

9789811518980


ISBN 10:   981151898
Pages:   432
Publication Date:   28 November 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Big Data Modelling and Methodology.- A constrained self-adaptive sparse combination representation method for abnormal event detection.- A Distributed Scheduling Framework of Service based ETL Process.- A Probabilistic Soft Logic Reasoning Model with Automatic Rule Learning.- Inferring How Novice Students Learn to Code: Integrating Automated Program Repair with Cognitive Model.- Predicting Friendship Using a Unified Probability Model.- Product Feature Extraction via Topic Model and Synonym Recognition Approach.- Vietnamese Noun Phrase Chunking Based on BiLSTM-CRF Model and Constraint Rules.- Big Data Support and Architecture.- A Distributed Big Data Discretization Algorithm under Spark.- A Novel Distributed Duration-aware LSTM for Large Scale Sequential Data Analysis.- Considering User Distribution and Cost Awareness to Optimize Server Deployment.- Convolutional Neural Networks on EEG-based Emotion Recognition.- Distributed Subgraph Matching Privacy Preserving Method for Dynamic Social Network.- Big Data Processing.- Clustering-Anonymization-Based Differential Location Privacy Preserving Protocol in WSN.- Distributed Graph Perturbation Algorithm on Social Networks with Reachability Preservation.- Minimum Spanning Tree Clustering Based on Density Filtering.- Research of CouchDB Storage Plugin for Big Data Query Engine Apache Drill.- Visual Saliency Based on Two-Dimensional Fractional Fourier Transform.- Big Data Analysis.- An Information Sensitivity Inference Method for Big Data Aggregation Based on Granular Analysis.- Attentional Transformer Networks for Target-Oriented Sentiment Classification.- Distributed Logistic Regression for Separated Massive Data.- Similarity Evaluation on Labeled Graphs via Hierarchical Core Decomposition.- Weighted Multi-label Learning with Rank Preservation.- Orthogonal Graph Regularized Nonnegative Matrix Factorization for Image Clustering.- Big Data Application.- Characteristics of Patient Arrivals and Service Utilization in Outpatient Departments.- College Academic Achievement Early Warning Prediction based on Decision Tree Model.- Intelligent Detection of Large-scale KPI Streams Anomaly Based on Transfer learning.- Latent Feature Representation for Cohesive Community Detection based on Convolutional Auto-Encoder.- Research on Monitoring Method of Ethylene Oxide Process by Improving C4.5 Algorithm.- Web API Recommendation with Features Ensemble and Learning-to-Rank.- EagleQR: An Application in Accessing Printed Text for the Elderly and Low Vision People.

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