Technical Programme

The following peer-reviewed scientific papers will be presented in the BDCAT 2018 main conference track. Underlined authors will be available to present and discuss their papers. Session chairs and substitute speakers are indicated.

Tuesday, December 18:

10.00 Big Data Infrastructures I (session chair: David Chiu)

  • Silvina Caíno-Lores, Jesús Carretero, Bogdan Nicolae, Orcun Yildiz and Tom Peterka: Spark-DIY: A Framework for Interoperable Spark Operations with High Performance Block-Based Data Models
  • Sarthak Kukreti and Frank Mueller: CloneHadoop: Process Cloning to Reduce Hadoop's Long Tail

11.30 Big Data Infrastructures II (session chair: Frank Muller)

  • Sam Burdick, Jahrme Risner, David Chiu and Jason Sawin: Fault-Tolerant Query Execution over Distributed Bitmap Indices
  • Guilherme F. Lima, Ahmad Slo, Sukanya Bhowmik, Markus Endler and Kurt Rothermel: Skipping Unused Events to Speed Up Rollback-Recovery in Distributed Data-Parallel CEP
  • Inanc Birol, Hamid Mohamadi and Justin Chu: ntPack: a software package for big data in genomics

15.00 Big Data Applications I (session chair: Andreas Weiler)

  • Richard Sinnott and Ziyue Guan: Prediction of Air Pollution through Machine Learning Approaches on the Cloud
  • Tamara Matthews, Muhammad Iqbal and Horacio Gonzalez-Velez: A comparative study of non-linear machine learning models with active sampling for MOX drift compensation

16.30 Big Data Applications II (session chair: Richard Sinnott)

  • Jongsun Lee, Hyun-Soo Choi, Yongkweon Jeon, Yongsik Kwon, Donghun Lee and Sungroh Yoon: Detecting System Anomalies in Multivariate Time Series with Information Transfer and Random Walk
  • Hui Yu, Yasunori Owada and Masato Oguchi: A Decentralized SNS System Based on XMPP with Connection Control in Large-Scale Disasters

Wednesday, December 19:

10.00 Big Data Analytics I (session chair: Richard Sinnott)

  • Muhammad Nauman Rafiq, Hasan Farooq, Ahmed Zoha and Ali Imran (presenter: Qi Zhao): Can Temperature Be Used as a Predictor of Data Traffic: A Real Network Big Data Analysis
  • Muawya Eldaw, Mark Levene and George Roussos: Presence Analytics: Making Sense of Humans Social Presence Within a Learning Environment

11.30 Big Data Analytics II (session chair: NN)

  • Chao Liu, Qi Zhao, Bai Yan, Saber Elsayed and Ruhul Sarker: An Improved Multi-Objective Evolutionary Approach for Clustering High-Dimensional Data
  • Maria Kotouza, Konstantinos Vavliakis, Fotis Psomopoulos and Pericles Mitkas: A hierarchical multi-metric framework for item clustering
  • Tao Yan, Chongzhao Han and Chengnan Wang: A Positive Approximation Set Based Accelerating Approach for Condition Attribute Reduction

16.30 Big Data Applications III (session chair: David Chiu)

  • Richard Sinnott, Fang Wu and Wenbin Chen: A Mobile Application for Dog Breed Detection and Recognition based on Deep Learning
  • Tsubasa Yamaguchi, Mansur As and Tsunenori Mine: Prediction of bus delay over intervals on a various kinds of routes using bus probe data

Thursday, December 20:

10.00 Big Data Applications IV (session chair: Ying Xie)

  • Alwin Yaoxian Zhang, Sean Shao Wei Lam, Nan Liu, Yan Pang, Ling Ling Chan and Phua Hwee Tang: Development of a Radiology Decision Support System for the Classification of MRI Brain Scans
  • Qidong Zhang, Yan Tang, Zequan Guo, Tingting Wu, Li Xu and Xiaofeng Gao: Adaptive General Event Popularity Analysis on Streaming Data

11.30 Big Data Applications V (session chair: Yan Tang)

  • Noufa Alnajran: An Empirical Performance Evaluation of Semantic-Based Similarity Measures in Microblogging Social Media
  • Zhenyu Wu, Jiaying Chen and Yinuo Zhang: An incremental community detection method in social big data
  • Claudio Atzori, Paolo Manghi and Alessia Bardi: GDup: De-duplication of Scholarly Communication Big Graphs

15.00 Big Data Applications VI (session chair: Yan Tang)

  • Youjun Zhang, Guanjun Liu, Lutao Zheng, Chungang Yan and Changjun Jiang: A novel method of processing class imbalance and its application in transaction fraud detection
  • Linh Le and Ying Xie: Recurrent Embedding Kernel for Predicting Stock Daily Direction

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