Workshop Sessions

BDM Technical Program
April 19, 2016 (Tuesday)
13:30 – 13:45 Opening and introduction to Bio-inspired data mining by Dr. Shafiq Alam
13:50 – 14:40 Keynote Talk : Prof. Mengjie Zhang, Recent Developments in Evolutionary Computation for Data Mining
14:40 – 15:00 Title: Towards a new evolutionary subsampling technique for heuristic optimization of load disaggregates
Authors: Michael Mayo and Sara Omranian
15:00 – 15:30 Coffee Break
15:30 – 15:50 Title: Neural Choice by Elimination via Highway Networks
Authors: Truyen Tran, Dinh Phung and Svetha Venkatesh
15:55 – 16:15 Title: Attribute Selection and Classification of Prostate Cancer Gene expression Data using Artificial Neural Networks
Authors: Sreenivas Sremath, Tirumala and Ajit Narayanan
16:20 – 16:40 Title: An Improved Self-Structuring Neural Network Method
Authors: Rami Mohammad, Fadu Thabtah and Lee McCluskey
16:45 – 17:05 Title: Imbalanced ELM Based on Normal Density Estimation for Binary-Class Classifications
Authors: Yulin He, Rana Aamir Raza Ashfaq, Joshua Zhexue Huang, and Xizhao Wang
17:10 – 17:30 Title: A New Multiple Seeds Based Evolutionary Algorithm for Mining Boolean Association Rules
Authors: Jahangir Kabir, Byeong Ho Kang, Shuxiang Xu, and Zongyuan Zhao
17:30 – Best Paper Award, Conclusions, and Closing by Prof. Gillian Dobbie

MLSDA Technical Program
April 19, 2016 (Tuesday)
08:45 – 09:00 Welcome & Opening Remarks (Bernhard Pfahringer)
09:00 – 10:00 Keynote Talk #1: Myra Spiliopoulou – Learning from Multiple Correlated Sensor Signals in Medical Research Applications

Intelligent sensor technology is widely used in healthcare. One goal is to assist patients with chronical diseases, e.g. by monitoring activity, recognizing emergencies and raising alerts. Before any use in healthcare, sensor technology is first tested in medical research, where the goals are to contribute to better diagnostics, to assess the effectiveness of some treatment or to design prevention measures. In this talk, I discuss examples of sensor mining for diagnostics and prevention.

The first example is on analyzing tumor enhancement kinetics in Dynamic Contrast-Enhanced Magnetic Resonance Images. Here, the goal of sensor mining is to distinguish between benign and malignant breast tumors. The relative enhancement curves differ, depending on whether a voxel belongs to a malignant region or not. However, the curve of any single voxel is not adequate to decide on malignancy. Signals from proximal voxels are evidently correlated, and this fact can (and should) be exploited to identify regions that exhibit similar enhancement curves.

The second example is on understanding how patients with diabetic foot syndrome apply plantar pressure. Medical research has shown that the likelihood of foot amputation among patients with diabetic foot syndrom is up to 40 times higher than among non-diabetics, that increased foot temperature may indicate the onset of an ulceration, and that plantar pressure modulates temperature. Intelligent wearables thus monitor pressure in different regions of the feet. Here, a goal of sensor mining is to derive pressure profiles, exploiting the correlation among proximal sensors, and to optimize the number and placement of sensors in the wearable.

10:00 – 10:30 Coffee Break
10:30 – 11:30 Session I – Sensory Data Analysis – Chair: Ashfaqur Rahman

• Predicting Phone Usage Behaviors with Sensory Data using Hierarchical Generative Model, by Chuankai An and Dan Rockmore

• Learning Multi-faceted Activities from Heterogeneous Data with the Product Space Hierarchical Dirichlet Processes, by Thanh Binh Nguyen, Vu Nguyen, Svetha Venkatesh and Dinh Phungy

11:30 – 12:30 Session II – Clustering and Applications – Chair: Yuan Jiang

• Image Segmentation With Superpixel Based Covariance Descriptor, by Xianbin Gu and Martin Purvis

• Phishing Detection on Twitter Streams using Unsupervised Learning, by Se Yeong Jeong, Yun Sing Koh and Gill Dobbie

• Rigidly Self-Expressive Sparse Subspace Clustering, by Linbo Qiao, Bo-Feng Zhang, Shiqian Ma and Jinshu Su

12:30 – 13:30 Lunch Break
13:30 – 14:30 Keynote Talk #2: Zhi-Hua Zhou – Learning Performance Optimization on Streaming Data
14:30 – 15:10 Session III – Action Recognition – Chair: Jeremiah Deng

• A Comparative Evaluation of Action Recognition Methods via Riemannian Manifolds, Fisher Vectors and GMMs: Ideal and Challenging Conditions, by Johanna Carvajal, Arnold Wiliem, Chris McCool, Brian Lovell and Conrad Sanderson

• Joint Recognition and Segmentation of Actions via Probabilistic Integration of Spatio-Temporal Fisher Vectors, by Johanna Carvajal, Chris McCool, Brian Lovell and Conrad Sanderson

15:10 – 15:30 Coffee Break
15:30 – 16:00 Prize-giving and Panel Session – Chair: Jiuyong Li

PACC Technical Program
April 19, 2016 (Tuesday)
08:30 – 08:45 Welcome
08:45 – 10:00 Keynote Address: Analysis of patient data: sign-posts for providing better healthcare

Professor Jim Warren, Chair in Health Informatics, Department of Computer Science, University of Auckland

10:00 – 10:30 Coffee Break
10:30 – 11:30 Paper Presentations (20 mins each)

  • Normalized Cross-Match: Pattern Discovery Algorithm from Biofeedback Signals
  • Event Prediction in Healthcare Analytics: Beyond Prediction Accuracy
  • Clinical Decision Support for Stroke using Multi-View Learning based Models for NIHSS Scores
11:30 – 12:30 Panel Discussion:

Topic: Use of medical domain knowledge for predictive analytics – Issues and Challenges

Distinguished Panel Members:

PAISI Technical Program
April 19, 2016 (Tuesday)
08:30 – 09:15 Opening and Keynote Speech
Session Chair: Michael ChauTitle: Cloud-Centric Assured Information Sharing
Professor Bhavani Thuraisingham ,The University of Texas at Dallas
09:15 – 10:05 Session 1: Network-Based Data Analytics
Session Chair: Michael Chau

  • The Use of Reference Graphs in the Entity Resolution of Criminal Networks
    David Robinson
  • Heterogeneous Information Networks Bi-Clustering with Similarity Regularization*
    Haixin Li, Xianchao Zhang, Wenxin Liang, Linlin Zong, and Xinyue Liu
10:05 – 10:30 Coffee Break
10:30 – 12:30 Session 2: Data and Text Mining
Session Chair: Joshua Wang

  • A Profile-Based Authorship Attribution Approach to Forensic Identification in Chinese Online Messages
    Jianbin Ma, Bing Xu, and Mengjie Zhang
  • Multilevel Syntactic Parsing based on Recursive Restricted Boltzmann Machines and Learning to Rank*
    Jungang Xu, Hong Chen, Shilong Zhou, and Ben He
  • Stratified Over-Sampling Bagging Method for Random Forests on Imbalanced Data*
    He Zhao, Xiaojun Chen, Tung Nguyen, Joshua Huang, Graham Williams, and Hui Chen
  • Revisiting Attribute Independence Assumption in Probabilistic Unsupervised Anomaly Detection*
    Sunil Aryal, Kai Ming Ting, and Gholamreza Haffari
12:30 – 13:30 Lunch Break
13:30 – 15:00 Session 3: Data and Text Mining
Session Chair: Přemysl Čech

  • Incremental Privacy-Preserving Association Rule Mining Using Negative Border
    Duc H. Tran, Wee Keong Ng, Yiik Diew Wong, and Vinh V. Thai
  • Differentially Private Multi-Task Learning
    Sunil Gupta, Santu Rana, and Svetha Venkatesh
  • Intelligent Recognition of Spontaneous Expression Using Motion Magnification of Spatio-Temporal Data
    B. M. S. Bahar Talukder, Brinta Chowdhury, Tamanna Howlader, and S. M. Mahbubur Rahman
15:00 – 15:30 Coffee Break
15:30 – Session 4: Cybersecurity and Infrastructure Protection
Session Chair: Daniel Hughes

  • k-NN Classification of Malware in HTTPS Traffic Using the Metric Space Approach
    Jakub Lokoč, Jan Kohout, Přemysl Čech, Tomáš Skopal, and Tomáš Pevný
  • A Syntactic Approach for Detecting Viral Polymorphic Malware Variants
    Vijay Naidu and Ajit Narayanan
  • Small State Acquisition of Offensive Cyberwarfare Capabilities: Towards Building an Analytical Framework*
    Daniel Hughes and Andrew Colarik
  • Data-Driven Stealthy Injection Attacks on Smart Grid with Incomplete Measurements*
    Adnan Anwar, Abdun Mahmood, and Mark Pickering
  • Information Security in Software Engineering, Analysis of Developers Communications about Security in Social Q&A Website*
    Shahab Bayati and Marzieh Heidary

*: short paper

WDMBF Technical Program
April 19, 2016 (Tuesday)
08:30 – 08:40 Workshop Opening: Welcome and Introduction to the Workshop
08:40 – 09:10 Title: Keystroke Biometric Recognition on Chinese Long Text Input
Authors: Xiaodong Li, Jiafen Liu
09:10 – 09:40 Title: A social spam detection framework via semi-supervised learning
Authors: Xianchao Zhang, Haijun Bai, Wenxin Liang
09:40 – 10:00 Title: Recommendation Algorithm Design in a Land Exchange Platform
Authors: Xubin Luo, Jiang Duan
10:00 – 10:30 Coffee Break
10:30 – 11:00 Title: Matching Product Offers of E-Shops
Authors: Andrea Horch, Holger Kett, Anette Weisbecker
11:00 – 11:30 Title: Efficient Iris Image Segmentation for ATM Based Approach through Fuzzy Entropy and Graph Cut
Authors: Shibai Yin, Yibin Wang, Tao Wang
11:30 – 12:00 Title: A hierarchical beta process approach for financial time series trend prediction
Authors: Mojgan Ghanavati, Raymond K. Wong, Fang Chen, Yang Wang, Joe Lee
12:00 – 12:30 Title: A Music Recommendation System Based on Acoustic Features and User Personalities
Authors: Rui Cheng, Boyang Tang