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ORCIDBigData Congress 2019: Milan, Italy
- Elisa Bertino, Carl K. Chang, Peter Chen, Ernesto Damiani, Michael Goul, Katsunori Oyama:
2019 IEEE International Congress on Big Data, BigData Congress 2019, Milan, Italy, July 8-13, 2019. IEEE 2019, ISBN 978-1-7281-2772-9
Security & Privacy
- Clemens Lachner
, Thomas Rausch, Schahram Dustdar:
Context-Aware Enforcement of Privacy Policies in Edge Computing. 1-6 - Piero A. Bonatti, Sabrina Kirrane:
Big Data and Analytics in the Age of the GDPR. 7-16 - Feng Xing, Caili Guo:
Mining Semantic Information in Rumor Detection via a Deep Visual Perception Based Recurrent Neural Networks. 17-23
Resource Management
- Paolo Missier, Jacek Cala:
Efficient Re-Computation of Big Data Analytics Processes in the Presence of Changes: Computational Framework, Reference Architecture, and Applications. 24-34 - Changxin Bai, Shiyong Lu, Ishtiaq Ahmed, Dunren Che, Aravind Mohan:
LPOD: A Local Path Based Optimized Scheduling Algorithm for Deadline-Constrained Big Data Workflows in the Cloud. 35-44 - Francesco Pace, Dimitrios Milios, Damiano Carra, Pietro Michiardi:
Dynamic Resource Shaping for Compute Clusters. 45-54
Applications
- Roberto Corizzo, Michelangelo Ceci, Donato Malerba:
Big Data Analytics and Predictive Modeling Approaches for the Energy Sector. 55-63 - Jianyang Yu, Yuanyuan Qiao, Nanfei Shu, Kewu Sun, Shenshen Zhou, Jie Yang:
Neural Network Based Transaction Classification System for Chinese Transaction Behavior Analysis. 64-71 - Luca Cagliero, Silvia Chiusano, Elena Daraio, Paolo Garza:
CarPredictor: Forecasting the Number of Free Floating Car Sharing Vehicles within Restricted Urban Areas. 72-76
Platform 1
- Daniel Peralta, Yvan Saeys:
Distributed, Numerically Stable Distance and Covariance Computation with MPI for Extremely Large Datasets. 77-84 - Michele Ciavotta, Srdjan Krstic, Damian A. Tamburri, Willem-Jan van den Heuvel:
HyperSpark: A Data-Intensive Programming Environment for Parallel Metaheuristics. 85-92 - Hourieh Khalajzadeh, Mohamed Abdelrazek, John Grundy, John G. Hosking, Qiang He:
BiDaML: A Suite of Visual Languages for Supporting End-User Data Analytics. 93-97
Analysis Methods 1
- Hui Gao, Karolina K. Dluzniak, Hong Xia, Wei Jie, Yanping Chen, Wei Xing, Xin Wang, Zhongmin Wang:
A Service Clustering Method Based on Wisdom of Crowds. 98-105 - Francesco Guerra, Paolo Sottovia, Matteo Paganelli, Maurizio Vincini:
Big Data Integration of Heterogeneous Data Sources: The Re-Search Alps Case Study. 106-110
Recommendations
- Boyuan Guan, Liting Hu, Pinchao Liu, Hailu Xu, Zhaohui Fu, Qingyang Wang:
dpSmart: A Flexible Group Based Recommendation Framework for Digital Repository Systems. 111-120 - Sara Migliorini, Elisa Quintarelli, Damiano Carra, Alberto Belussi:
Sequences of Recommendations for Dynamic Groups: What Is the Role of Context? 121-128 - Chia-Hsuan Chang, Ming-Lun Wu, San-Yih Hwang:
An Approach to Cross-Lingual Sentiment Lexicon Construction. 129-131
Prediction
- Junyao Guo, Lu Liu, Sihai Zhang, Jinkang Zhu:
Mobility Prediction with Missing Locations Based on Modified Markov Model for Wireless Users. 132-138 - Stefano Proto, Francesco Ventura, Daniele Apiletti, Tania Cerquitelli, Elena Baralis, Enrico Macii, Alberto Macii:
PREMISES, a Scalable Data-Driven Service to Predict Alarms in Slowly-Degrading Multi-Cycle Industrial Processes. 139-143 - Francesco Ventura, Stefano Proto, Daniele Apiletti, Tania Cerquitelli, Simone Panicucci, Elena Baralis, Enrico Macii, Alberto Macii:
A New Unsupervised Predictive-Model Self-Assessment Approach That SCALEs. 144-148
Platform 2
- Nesma Mahmoud, Youssef Essam, Radwa El Shawi, Sherif Sakr:
DLBench: An Experimental Evaluation of Deep Learning Frameworks. 149-156 - Mahmoud Ismail, August Bonds, Salman Niazi, Seif Haridi, Jim Dowling:
Scalable Block Reporting for HopsFS. 157-164 - Anna Levin, Shelly Garion, Elliot K. Kolodner, Dean H. Lorenz, Katherine Barabash, Mike Kugler, Niall McShane:
AIOps for a Cloud Object Storage Service. 165-169
Analysis Methods 2
- Fan Yang, Adina Crainiceanu, Zhiyuan Chen, Don Needham:
Cluster-Based Join for Geographically Distributed Big RDF Data. 170-178 - Haojie Huang, Raymond K. Wong:
Reducing Feature Embedding Data for Discovering Relations in Big Text Data. 179-183
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