DSAT 2018-07-17T18:57:16+00:00

DSAT: Data Sciences, Analytics & Technologies

The Data Sciences, Analytics, and Technologies (DSAT) Symposium is an integral part of the overall IEEE COMPSAC conference. Complementing the COMPSAC theme “Staying Smarter in a Smartening World,” DSAT uniquely positions itself as a forum for both researchers and practitioners in Big Data as it relates to data sciences, data analytics, and associated technologies.  DSAT invites authors to present recent findings, innovations, theories, experiences, and ideas. Technical contributions accepted by DSAT will likely cover theory, applications, pragmatics, systems and services enabled by the Web, underlying technologies, data science, e-science, and concomitant big data analytics. The goal of DSAT is to deepen the understanding of, fostering innovation in, and sharing of practical applications around Big Data.

Topic areas to include, but not limited to: Applied data science, Anomaly detection, computational intelligence for Big Data analytics, Business analytics, Business informatics, Data information and knowledge, Data mining, Data warehousing, Exploring and visualizing data, Interactive visualization, Modeling and simulation, Privacy, and Security. Consider potential focus with the interconnected relationships of Big Data, Cloud, Fog, Edge Computing, IoT, mobile computing, and pervasive computing.

Some authors will be invited to submit expanded papers for the IEEE Transactions on Big Data journal COMPSAC special issue.

DSAT Symposium Schedule

Tuesday July 24, 11:00 – 12:30pm
Session 1
Location: Meeting Hall 4
Session Chair: Wo Chang, National Institute of Standards and Technology (NIST), USA

Knowledge Map Construction Using Text Mining and Artificial Bee Colony Algorithm
Chieh-Yuan Tsai, Wei-Zhong Ji

Mining Rules from Real-valued Time Series: A Relative Information-Gain-based Approach
Yuanduo He, Guangju Peng, Xu Chu, Yasha Wang, Zhu Jin, Xiaorong Wang

World Grid Square Data Reference Framework and its Potential Applications
Aki-Hiro Sato, Shoki Nishimura, Hiroe Tsubaki, Tsuyoshi Namiki

Tuesday July 24, 1:30 – 3:00pm
Session 2
Location: Meeting Hall 4
Session Chair: Jie Li, University of Tsukuba, Japan

A Local Cores-based Hierarchical Clustering Algorithm for Data Sets with Complex Structures
Dongdong Cheng, Qingshen Zhu, Quanwang Wu

Web Items Recommendation Based on Multi-view Clustering
Hong Yu, Tiantian Zhang, Jiaxin Chen, Chen Guo, Yahong Lian
Characterizing Common and Domain-specific Package Bugs: A Case Study on Ubuntu
Xiaoxue Ren, Qiao Huang, Xin Xia, Zhenchang Xing, Lingfeng Bao, David Lo

Tuesday July 24, 3:30 – 5:00pm
Session 3
Location: Meeting Hall 4
Session Chair: Tsung Teng Chen, National Taipei University, Taiwan

Deciphering the Big Data Research Themes
Tsung Teng Chen, Maria Lee

Towards Lambda-based Near Real-time OLAP over Big Data
Alfredo Cuzzocrea, Rim Moussa

Characterizing Incidents in Cloud-based IoT Data Analytics
Hong-Linh Truong, Manfred Halper

Efficient Discovery of Traveling Companion from Evolving Trajectory Data Stream
Thi Thi Shein, Sutheera Puntheeranurak, Makoto Imamura

Wednesday July 25, 11:00 – 12:30pm
Session 4
Location: Meeting Hall 4
Session Chair: May Wang, Georgia Institute of Technology, USA

A Software Popularity Recommendation Method Based on Evaluation Model
Yan Wang, Peixiang Bai, Deyu Yang, Jiantao Zhou, Xiaoyu Song

Analysis and Prediction of Endoresement-based Skill Assessment in LinkedIn
Yan Wu, Nitish Dhakal, Diaxiang Xu, Jin-Hee Cho

An Improved Promoter Recognition Model Using Convolutional Neural Network
Ying Qian, Yu Zhang, Sasha Ye, Bingyu Guo, Yuzhu Wu, Jiongmin Zhang

IT Professional 20th Anniversary Panel
San Murugesan, BRITE Professional Services, Australia

Thursday July 26, 11:00 – 12:30pm
Session 5
Location: Meeting Hall 4
Session Chair: Maria Lee, Shih Chien University, Taiwan

A Deep Learning Based Approach Based on Stacked Denoising Autoencoders for Protein Function Prediction
Lester James Miranda, Jinglu Hu

Faster Deep Q-learning Using Neural Episodic Control
Daichi Nishio, Satoshi Yamane

Automated Dental Image Analysis by Deep Learning on Small Dataset
Jie Yang, Yuchen Xie, Lin Liu, Bin Xia, Zhangqiang Cao, Chuanbin Guo

A Service-oriented Approach to Modeling and Reusing Event Correlations
Meiling Zhu, Chen Liu, Yanbo Han

Thursday July 26, 1:30 – 3:30pm
Session 6
Location: Meeting Hall 4
Session Chair: Kathy Grise, IEEE

Elucidating Which Pairwise Mutations Affect Protein Stability: An Exhaustive Big Data Approach
Nicholas Majeski, Filip Jagodzinski

DLCEncDec: A Fully Character-level Encoder-Decoder Model for Neural Responding Conversation
Sixing Wu, Ying Li, Xinyuan Zhang, Zhonghai Wu

BDViewer – A Web-based Big Data Processing and Visualization Tool
Yan Li, Junming Ma, Bo An, Donggang Cao

Optimising Toward Completed Videos in an Online Video Advertising Exchange
Douglas McIlwraith, Andrea Catalucci, Sam Boyd, Raouf Aghrout, Yi-ke Guo

Paper submission for COMPSAC symposia are now closed.

Deadlines and due dates are available on the Important Dates page.

Paper templates and additional information for authors is available on the Information for Authors page.

DSAT Symposium Co-chairs

Kathy Grise, IEEE Future Directions, USA
Email: k.l.grise@ieee.org
Maria Lee, Shih Chien University, Taiwan
Email: maria.lee@g2.usc.edu.tw

Technical Program Chairs

Tsung Teng Chen, National Taipei University, Taiwan
Jie Li, University of Tsukuba, Japan

DSAT Program Committee

To be announced