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6th BDCAT 2019: Auckland, New Zealand
- Kenneth Johnson, Josef Spillner
, Xinghui Zhao, Olga Datskova, Blesson Varghese:
Proceedings of the 6th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies, BDCAT 2019, Auckland, New Zealand, December 2-5, 2019. ACM 2019, ISBN 978-1-4503-7016-5
Session 1: Data Processing I
- Samuel Armstrong, Kevin Bruhwiler, Sangmi Lee Pallickara:
Rapid, Progressive Sub-Graph Explorations for Interactive Visual Analytics over Large-Scale Graph Datasets. 1-10 - Mitchell Nelson, Zachary Sorenson, Joseph M. Myre, Jason Sawin, David Chiu:
GPU Acceleration of Range Queries over Large Data Sets. 11-20 - Taehee Jeong, Deeksha Prakash Kankalale, Raymond Chau, Hyeran Jeon:
Going Deeper or Wider: Throughput Prediction for Cluster Tools with Machine Learning. 21-30 - Kazuhiro Serizawa, Osamu Tatebe:
Accelerating Machine Learning I/O by Overlapping Data Staging and Mini-batch Generations. 31-34
Session 2: Social Networks
- Yan Pang, Ganeshkumar Sundararaj, Jiewen Ren:
Cryptocurrency Price Prediction using Time Series and Social Sentiment Data. 35-41 - Mihira Wanninayake, Richard O. Sinnott:
An Exploration of Commuter Travel Time Through Social Media Analytics on the Cloud. 43-51 - Amir Jalalirad, Marco Scavuzzo, Catalin Capota, Michael R. Sprague:
A Simple and Efficient Federated Recommender System. 53-58 - Nagaraju Vadranam, K. M. George, Starla Marier Demings:
An Analysis of Slant in Tweets: Case Study. 59-62
Session 3A: Machine Learning
- Peng Zhao, Xinrui Lyu, Richard O. Sinnott, Shimin Wei:
Crowd-Counting through a Cascaded, Multi-Task Convolutional Neural Network. 63-66 - Jie Liu, Yan Tang, Xinyi Xu:
HISDOM: A Hybrid Ontology Mapping System based on Convolutional Neural Network and Dynamic Weight. 67-70
Session 3B: Data Processing II
- Chandan Sharma
A Schema-First Formalism for Labeled Property Graph Databases: Enabling Structured Data Loading and Analytics. 71-80 - Chun-Yu Wang
A Data Compacting Technique to reduce the NetFlow size in Botnet Detection with BotCluster. 81-84
Session 4: Big Data Applications I
- Sota Kato
Topic Variation Detection Method for Detecting Political Business Cycles. 85-93 - Alwin Yaoxian Zhang, Sean Shao Wei Lam, Marcus Eng Hock Ong, Phua Hwee Tang, Ling Ling Chan
Explainable AI: Classification of MRI Brain Scans Orders for Quality Improvement. 95-102 - Marianne Cherrington, David Airehrour, Joan Lu
Feature Selection Methods for Linked Data: Limitations, Capabilities and Potentials. 103-112 - Tao Yan, Chongzhao Han, Yong Jia:
A Fused Intelligent Computing Approach Using Stock Big Data for Near Future Trend Prediction. 113-116
Session 5: Deep Learning
- Lu Chen, Yunjie Jia, Pei-Yun Sun, Richard O. Sinnott:
Identification and Classification of Trucks and Trailers on the Road Network through Deep Learning. 117-126 - Priyanthi M. Dassanayake
A Deep Reinforcement Learning based Homeostatic System for Unmanned Position Control. 127-136 - Yuncheng Jin, Zhihong Chen, Zhaowei Cheng, Chao Chen, Xinyu Jin, Bin Sun:
Class-Level Adaptation Network with Self Training for Unsupervised Domain Adaptation. 137-143 - Huaqing Yu, Shining Song, Shaoxi Ma, Richard O. Sinnott:
Estimating Fruit Crop Yield through Deep Learning. 145-148
Session 6: Big Data Applications II
- Musen Wen, Deepak Kumar Vasthimal, Alan Lu, Tian Wang, Aimin Guo:
Building Large-Scale Deep Learning System for Entity Recognition in E-Commerce Search. 149-154 - Takuto Sato, Osamu Tatebe, Hiroyuki Kusaka:
In-situ Data Analysis System for High Resolution Meteorological Large Eddy Simulation Model. 155-158 - Henrique Varella Ehrenfried
Managing Open Data Evolution through Bi-dimensional Mappings. 159-162
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