Conference Program

Program Overview

(tentative)







To presenters: small changes might be made closer to the conference dates *without* notice.

Long paper presentation: 30 mins (including Q&A)

Short paper presentation: 20 mins (including Q&A)


June 3, 2018 (Sunday)

08:00

08:30

Registration

 

 

Mayfair 1 (300)

Mayfair 2 (80)

Mayfair 3 (80)

Grosvenor 1 (40)

Grosvenor 2 (40)

08:30

10:00

Tutorial
Deep Learning for Biomedical Discovery and Data Mining (Truyen Tran)
(Chair: TBA)

Workshop

BDM
6th Workshop on Biologically Inspired Data Mining Technique

(Chair: TBA)

Workshop

ML4Cyber
Australasian Workshop on Machine Learning for Cyber-security

(Chair: TBA)

Workshop

BDASC
Big Data Analytics for Social Computing

(Chair: TBA)

Workshop

PAISI
The 12th Pacific Asia Workshop on Intelligence and Security Informatics

(Chair: TBA)

10:00

10:30

Coffee Break

10:30

12:00

Tutorial
Deep Learning for Biomedical Discovery and Data Mining (Truyen Tran)
(Chair: TBA)

Workshop

BDM
6th Workshop on Biologically Inspired Data Mining Technique

(Chair: TBA)

Workshop

ML4Cyber
Australasian Workshop on Machine Learning for Cyber-security

(Chair: TBA)

Workshop

BDASC
Big Data Analytics for Social Computing

(Chair: TBA)

 

 

 

Workshop

PAISI
The 12th Pacific Asia Workshop on Intelligence and Security Informatics

(Chair: TBA)

12:00

13:30

Lunch

13:30

15:30

Tutorial

Relevant
Structure Search in Graph Databases: Methods and Applications (Yuanyuan Zhu, Xin Huang)

(Chair: TBA)



Workshop
DaMEMO
Data Mining for Energy Modeling and Optimization
(Chair: TBA)

Workshop
BDASC

Big Data Analytics for Social Computing
(Chair: TBA)

Workshop
PAISI
The 12th Pacific Asia
Workshop on Intelligence and Security Informatics
(Chair: TBA)

15:30

16:00

Coffee Break

16:00

18:00


Workshop
DaMEMO
Data Mining for Energy Modeling and Optimization
(Chair: TBA)

Workshop
BDASC
Big Data Analytics for
Social Computing
(Chair: TBA)

Workshop
PAISI
The 12th Pacific Asia
Workshop on Intelligence and Security Informatics
(Chair: TBA)

18:00

20:00

Welcome Reception

June 4, 2018 (Monday)

08:00

08:30

Registration

08:30

09:00

Conference Opening (Mayfair)

09:00

10:00

Keynote Speech
Topic for presentation is to be announced
(Chair: TBA)

10:00

10:15

Coffee Break

 

 

Mayfair 1 (300)

Mayfair 2 (80)

Mayfair 3 (80)

Grosvenor (80)

13:30

15:30

Research
Classification and supervised machine learning (Part 1)
(Chair: TBA)

Research
Healthcare, Bioinformatics and Related Topics (Application) (Part 1)
(Chair: TBA)

Research
Human, Behaviour and Interactions (Application)
(Part 1)

(Chair: TBA)

Research

Opinion
Mining and Sentiment Analysis

(Chair: TBA)

12:15

13:30

Lunch

13:30

15:30

Research
Classification and supervised machine learning (Part 2)
(Chair: TBA)

Research
Healthcare, Bioinformatics and Related Topics (Application) (Part 2)
(Chair: TBA)

Research
Human, Behaviour and Interactions (Application)
(Part 2)

(Chair: TBA)

Research
Graphical models, latent variables and statistical methods(Part 1)
(Chair: TBA)

15:30

16:00

Coffee Break

15:45

18:00

Research
Classification and supervised machine learning (Part 3)
(Chair: TBA)

Research
Healthcare, Bioinformatics and Related Topics (Application) (Part 3)
(Chair: TBA)

Research
Anomaly detection and analytics
(Chair: TBA)

Research
Graphical models, latent variables and statistical methods (Part 2)
(Chair: TBA)

June 5, 2018 (Tuesday)

08:30

09:00

Registration

09:00

10:00

Keynote Speech
Machine Learning @ Amazon
(Dr Rajeev Rastogi)
(Chair: TBA)

10:00

10:15

Coffee Break

10:15

12:15

Research
Representation Learning and Embedding (Part 1)
(Chair: TBA)

Research
Semi-Structured Data and NLP (Part 1)
(Chair: TBA)

Research
Spatial-Temporal, Time-series and Stream Mining (Part 1)
(Chair: TBA)

Research
Feature Learning and Data Mining Process (Part 1)
(Chair: TBA)

12:15

13:30

Lunch

13:30

15:30

Research
Representation Learning and Embedding (Part 2)
(Chair: TBA)

Research
Semi-Structured Data and NLP (Part 2)
(Chair: TBA)

Research
Spatial-Temporal, Time-series and Stream Mining (Part 2)
(Chair: TBA)

Research
Feature Learning and Data Mining Process (Part 2)
(Chair: TBA)

15:30

16:00

Coffee Break

16:00

18:00

Research
Social Network, Ubiquitous Data and Graph Mining (Part 1)
(Chair: TBA)

Research
Community Detection and Network Science
(Chair: TBA)

Research
Spatial-Temporal, Time-series and Stream Mining (Part 3)
(Chair: TBA)

Research
Feature Learning and Data Mining Process (Part 3)
(Chair: TBA)

18:15

22:00

Banquet
(Award Announcement, PAKDD19 introduction)

June 6, 2018 (Wednesday)

09:00

10:00

Keynote Speech
Continuous Machine Learning
(Professor Bing Liu)
(Chair: TBA)

10:00

10:15

Coffee Break

10:15

12:15

Research
Deep Learning Theory and Applications in KDD (Part 1)
(Chair: TBA)

Research
Clustering and Unsupervised Learning (Part 1)
(Chair: TBA)

Research
Privacy-Preserving and Security
(Chair: TBA)

Research
Social Network, Ubiquitous Data and Graph Mining (Part 2)
(Chair: TBA)

12:15

13:30

Lunch

13:30

14:30

Data Competition
Data Competition Presentation and Award
(Chair: TBA)

13:30

14:45

Coffee Break

14:45

16:45

Research
Deep Learning Theory and Applications in KDD (Part 2)
(Chair: TBA)

Research
Clustering and Unsupervised Learning (Part 2)
(Chair: TBA)

Research
Recommendation and Data Factorization
(Chair: TBA)

Research
Social Network, Ubiquitous Data and Graph Mining (Part 3)
(Chair: TBA)

16:45

17:00

Conference Closing

 

 

Research Sessions


Classification and supervised machine learning (Part 1)
10:15 – 10:45 Classifier Risk Estimation under Limited Labeling Resources
Anurag Kumar*, Carnegie Mellon University; Bhiksha Raj, Carnegie Mellon University
10:45 – 11:15 Social Stream Classification with Emerging New Labels
Xin Mu*, Nanjing university; Feida Zhu, Singapore Management University; Yue Liu, Singapore Management University; Ee-peng Lim, Singapore Management University; Zhi-Hua Zhou, Nanjing university
11:15 – 11:35 Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules
Michael Rapp, TU Darmstadt; Eneldo Loza Mencia*, TU Darmstadt; Johannes Fürnkranz, TU Darmstadt
11:35 – 11:55 Modeling Label Interactions in Multi-label Classification: A Multi-structure SVM Perspective
Anusha Kasinikota, DXC Technology; Balamurugan Palaniappan*, IIT Bombay; Shirish Shevade, iisc
11:55 – 12:15 Sentiment Classification Using Neural Networks with Sentiment Centroids
maoquan wang*, East China Normal University; chen shiyun, East China Normal University; Liang He, ECNU
Classification and supervised machine learning (Part 2)
13:30 – 13:50 Random Pairwise Shapelets Forest
Jidong Yuan*, Beijing Jiaotong University; Zhihai Wang, Beijing Jiaotong University; Haiyang Liu, Beijing Jiaotong University; Mohan Shi, Beijing Jiaotong University
13:50 – 14:10 A Locally Adaptive Multi-Label k-Nearest Neighbor Algorithm
Dengbao Wang, College of Computer and Information Science, Southwest University; Jingyuan Wang, Southwest University; Fei Hu, Southwest University; Li LI*, Southwest University; Xiuzhen Zhang, RMIT University
14:10 – 14:30 Classification With Reject Option Using Conformal Prediction
Henrik Linusson*, University of Borås; Ulf Johansson, Jönköping University; Tuwe Löfström, Jönköping University; Henrik Boström, KTH Royal Institute of Technology
14:30 – 14:50 Target Learning: A Novel Framework to Mine Significant Dependencies for Unlabeled Data
Limin Wang*, Jilin University; Shenglei Chen, Nanjing Audit University; Musa Mammadov, Federation University
14:50 – 15:10 Automatic Chinese Reading Comprehension Grading by LSTM with Knowledge Adaptation
Yuwei Huang, Beijing University of Chemical Technology;Beijing Advanced Innovation Center For Future Education,Beijing Normal University; Xi Yang*, Beijing Advanced Innovation Center For Future Education,Beijing Normal University; Fuzhen Zhuang, Institute of Computing Technology, Chinese Academy of Sciences; Lishan Zhang, Beijing Advanced Innovation Center For Future Education,Beijing Normal University; Shengquan Yu, Beijing Advanced Innovation Center For Future Education,Beijing Normal University
15:10 – 15:30 Data Mining with Algorithmic Transparency
Yan Zhou*, UT Dallas; Yasmeen Alufaisan, UT Dallas; Murat Kantarcioglu, UT Dallas
Classification and supervised machine learning (Part 3)
15:45 – 16:05 Cost-Sensitive Reference Pair Encoding for Multi-Label Learning
Yao-Yuan Yang, National Taiwan University; Kuan-Hao Huang, National Taiwan University; Chih-Wei Chang, Carnegie Mellon University; Hsuan-Tien Lin*, National Taiwan University
16:05 – 16:25 Fuzzy Integral Optimization with Deep Q-Network for EEG-based Intention Recognition
Dalin Zhang*, UNSW Sydney; Lina Yao, UNSW; Sen Wang, Griffith University; Kaixuan Chen, UNSW Sydney; Zheng Yang, Tsinghua University; Boualem Benatallah, UNSW Sydney
16:25 – 16:45 Heterogeneous Domain Adaptation Based on Class Decomposition Schemes
Firat Ismailoglu, Maastricht University; Evgueni Smirnov*, Maastricht University; Ralf Peeters, Maastricht University; Shuang Zhou, Maastricht University; Pieter Collins , Maastricht University
16:45 – 17:05 A Deep Neural Spoiler Detection Model using a Genre-Aware Attention Mechanism
Buru Chang, Korea University, Data mining & Information systems labortory; Hyunjae Kim, DMIS; RAE HYUN KIM, KOREA UNIVERSITY; daehan kim, korea university; Jaewoo Kang*, Korea University
17:05 – 17:25 Robust Semi-Supervised Learning on Multiple Networks with Noise
Junting Ye*, Stony Brook University; Leman Akoglu, Carnegie Mellon University
17:25 – 17:45 e-Distance Weighted Support Vector Regression
Ge Ou*, Jilin University; Yan Wang, Jilin University; Lan Huang, CS Department, Jilin University; Wei Pang, University of Aberdeen; George Macleod Coghill, University of Aberdeen
Healthcare, BioInformatics and Related Topics (Application) (Part 1)
10:15 – 10:45 Corrosion Prediction on Sewer Networks with Sparse Monitoring Sites: A Case Study
Jianjia Zhang*, CSIRO; Bin Li, Fudan University; Xuhui Fan, UNSW; Yang Wang, Data61, CSIRO; Fang Chen, CSIRO
10:45 – 11:15 CAPED: Context-Aware Powerlet-based Energy Disaggregation
Jingyue Gao, Peking University; Yasha Wang*, Peking University; Xu Chu, Peking University; Yuanduo He, Peking University; Ziqing Mao, Peking University
11:15 – 11:35 Rolling Forecasting Forward by Boosting Heterogeneous Kernels
Di Zhang*, Communication University of China; Yunquan Zhang, State Key Lab of Computer Architecture, Institute of Computing Technology, Chinese Academy of Sciences; Qiang Niu, Department of Mathematical Sciences, Xi’an Jiaotong-Liverpool University; Xingbao Qiu, China Mobile Communications Corporation
11:35 – 11:55 IDLP: A Novel Label Propagation Framework For Disease Gene Prioritization
Yaogong Zhang*, NanKai University
11:55 – 12:15 Deep Learning for Forecasting Stock Returns in the Cross-Section
Masaya Abe*, Nomura Asset Management Co.,Ltd.; Hideki Nakayama, The University of Tokyo
Healthcare, BioInformatics and Related Topics (Application) (Part 2)
13:30 – 14:00 Vine Copula-based Asymmetry and Tail Dependence Modeling
Jia Xu*, University of Technology, Sydney; Longbing Cao, University of Technology Sydney
14:00 – 14:30 Detecting forged alcohol non-invasively through vibrational spectroscopy and machine learning
James Large*, University of East Anglia; Kate Kemsley, The Quadram Institute; Nikolaus Wellner, The Quadram Institute; Ian Goodall, Scotch Whisky Research Institute; Anthony Bagnall, University of East Anglia
14:30 – 14:50 Research and Application of Mapping Relationship based on Learning Attention Mechanism
Wanwan Jiang*, Shanghai University; Lingyu Xu, Shanghai University; Jie Yu, Shanghai University; Gaowei Zhang, Shanghai University
14:50 – 15:10 Human Identification via Unsupervised Feature Learning from UWB Radar Data
Jie Yin*, The University of Sydney; Son Tran, The Australian E-Health Research Centre, CSIRO; Qing Zhang, The Australian E-Health Research Centre, CSIRO
15:10 – 15:30 Prescriptive Analytics through Constrained Bayesian Optimization
Haripriya Harikumar*, Deakin University; Santu Rana, Deakin University, Australia; Sunil Gupta, Deakin University, Australia; Thin Nguyen, Deakin University; Ramachandra Kaimal, Amrita University; Svetha Venkatesh, Deakin University
Healthcare, BioInformatics and Related Topics (Application) (Part 3)
15:45 – 16:05 Neighborhood Constraint Matrix Completion for Drug-Target Interaction Prediction
Xin Fan*, Nankai University; Yuxiang Hong, Nankai University; Xiaohu Liu, NanKai University; Yaogong Zhang, NanKai University; MaoQiang Xie, NanKai Universiy
16:05 – 16:25 Detecting Hypopnea and Obstructive Apnea Events using Convolutional Neural Networks on Wavelet Spectrograms of Nasal Airflow
Stephen McCloskey*, The University of Sydney; Rim Haidar, The University of Sydney; Irena Koprinska, University of Sydney; Bryn Jeffries, The University of Sydney
16:25 – 16:45 Deep Ensemble Classifiers and Peer Effects Analysis for Churn Forecasting in Retail Banking
Yuzhou Chen*, Southern Methodist University; Yulia Gel, The University of Texas at Dallas; Vyacheslav Lyubchich, UMCES; Todd Winship, Temenos Group
16:45 – 17:05 GBTM: Graph Based Troubleshooting Method for Handling Customer Cases Using Storage System Log
Subhendu Khatuya*, IIT KHARAGPUR; Ajay Bakshi, NetApp; Jayanta Basak, NetApp; Niloy Ganguly, IIT Kharagpur; Bivas Mitra, Indian Institute of Technology Kharagpur
17:05 – 17:25 Fusion of Modern and Tradition: A Multi-Stage-Based Deep Network Approach for Head Detection
Chih-Chieh Hung*, Tamkang university; Fu-Chun Hsu , The University of Melbourne
17:25 – 17:55 Learning Treatment Regimens from Electronic Medical Records
Hung Hoang*, Japan Advanced Institute of Science and Technology; Tu Bao Ho, JAIST
Human, Behaviour and Interactions (Application) (Part 1)
10:15 – 10:45 Mining POI Alias from Microblog Conversations
Yihong Zhang*, Kyoto University; Lina Yao, UNSW
10:45 – 11:15 DyPerm: Maximizing Permanence for Dynamic Community Detection
Prerna Agarwal, IBM Research; Richa Verma, IIIT Delhi; Ayush Agarwal, IIIT Delhi; Tanmoy Chakraborty*, IIIT Delhi, India
11:15 – 11:35 Mining User Behavioral Rules from Smartphone Data through Association Analysis
Iqbal Sarker*, Swinburne University of Technology; Flora Salim, RMIT University
11:35 – 11:55 A Context-aware Evaluation Method of Driving Behavior
Yikai Zhai, Beihang University; Tianyu Wo*, Beihang University; Xuelian Lin, Beihang University; Zhou Huang, Beihang University; Junyu Chen, Tsinghua University
11:55 – 12:15 Measurement of Users’ Experience on Online Platforms from their Behavior Logs
Deepali Jain, Adobe Research; Atanu R. Sinha*, Adobe Research; Deepali Gupta, IIT Delhi; Nikhil Sheoran, IIT Roorkee; Sopan Khosla, Adobe Research
Human, Behaviour and Interactions (Application) (Part 2)
13:30 – 14:00 Mining Human Periodic Behaviors using Mobility Intention and Relative Entropy
feng Yi*, Institute of Information Engineering, Chinese Academy of Sciences; Libo Yin, China Industrial Control Systems Cyber Emergency Response Team; Hui Wen, Institute of information Engineering, CAS; Hongsong Zhu, Institute of information Engineering, CAS; Limin Sun, Institute of Information Engineering, Chinese Academy of Sciences; Bo Jiang, IIE,CAS
14:00 – 14:30 Context-Uncertainty-Aware Chatbot Action Selection via Parameterized Auxiliary Reinforcement Learning
Chuandong Yin*, The University of Melbourne; Rui Zhang, ” University of Melbourne, Australia”; Jianzhong Qi, The University of Melbourne; Yu Sun, University of Melbourne; Tan Tenglun, The University of Melbourne
14:30 – 14:50 Learning Product Embedding from Multi-relational User Behavior
Zhao Zhang*, PEKING UNIVERSITY; Weizheng Chen, PEKING UNIBERSITY; Xiaoxuan Ren, Peking University; Yan Zhang, Peking University
14:50 – 15:10 Vulnerability Assessment of Metro Systems Based on Dynamic Network Structure
Jun Pu, Computer Network Information Center, Chinese Academy of Sciences; Chuanren Liu, Drexel University; Jianghua Zhao, Computer Network Information Center, Chinese Academy of Sciences; Ke Han, Imperial College London; Yuanchun Zhou*, Computer Network Information Center, Chinese Academy of Sciences
15:10 – 15:30 Visual Relation Extraction via Multi-modal Translation Embedding Based Model
Zhichao Li*, BUPT; Yuping Han, BUPT; Yajing Xu, Beijing University of Posts and Telecommunications; Sheng Gao, BUPT
Anomaly detection and analytics
15:45 – 16:15 Sub-trajectory- and Trajectory-Neighbor-based Outlier Detection over Trajectory Streams
zhihua zhu*, Institute of Computing Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences; di yao, Institute of Computing Technology, Chinese Academy of Sciences; jianhui huang, Institute of Computing Technology, Chinese Academy of Sciences; jingping bi, Institute of Computing Technology, Chinese Academy of Sciences; Hanqiang Li, National Defence Key Laboratory of Blind Processing of Signals, Chengdu, China
16:15 – 16:35 An Unsupervised Boosting Strategy for Outlier Detection Ensembles
Guilherme Campos*, UFMG; Arthur Zimek, University of Southern Denmark; Wagner Meira Jr., UFMG
16:35 – 16:55 DeepAD: A Generic Framework based on Deep Learning for Time Series Anomaly Detection
Teodora Sandra Buda*, IBM; Bora Caglayan, IBM ; Haytham Assem, IBM
16:55 – 17:15 Anomaly detection technique robust to units and scales of measurement
Sunil Aryal*, Federation University
17:15 – 17:35 Automated Explanations of User-expected Trends for Aggregate Queries
Ibrahim Ibrahim*, University of Queensland; Xue Li, University of Queensland; Xin Zhao, University of Queensland; Sanad AL Maskari, University of Queensland; Abdullah Albarrak, University of Queensland; Yanjun Zhang, University of Queensland
17:35 – 17:55 Social Spammer Detection: A Multi-Relational Embedding Approach
Jun Yin, University of Technology Sydney; Zili Zhou, University of Technology Sydney; Shaowu Liu, University of Technology Sydney; Zhiang Wu*, Nanjing University of Finance and Economics; Guandong Xu, University of Technology Sydney, Australia
Opinion Mining and Sentiment Analysis
10:15 – 10:35 Learning to Rank Items of Minimal Reviews using Weak Supervision
Yassien Shaalan*, RMIT; Xiuzhen Zhang, RMIT University; Jeffrey Chan, RMIT University, Australia
10:35 – 10:55 Multimodal Mixture Density Boosting Network for Personality Mining
Nhi Vo*, University of Technology Sydney; Shaowu Liu, University of Technology Sydney; Guandong Xu, University of Technology Sydney, Australia; Xuezhong He, University of Technology Sydney
10:55 – 11:25 Identifying Singleton Spammers via Spammer Group Detection
Dheeraj Kumar, Purdue University; Yassien Shaalan, RMIT; Xiuzhen Zhang*, RMIT University; Jeffrey Chan, RMIT University, Australia
11:25 – 11:45 Adaptive Attention Network for Review Sentiment Classification
Chuantao Zong, Sun Yat-sen University; Wenfeng Feng, Sun Yat-sen University; Vincent W. Zheng, Advanced Digital Sciences Center; Hankui Zhuo*, Sun Yat-sen University
11:45 – 12:15 Cross-Domain Sentiment Classification via A Bifurcated-LSTM
Jinlong Ji*, Case Western Reserve University; Changqing Luo, Case Western Reserve University; Xuhui Chen, Case Western Reserve University; Lixing Yu, Case Western Reserve University; Pan Li, Case Western Reserve University
Graphical models, latent variables and statistical methods (Part 1)
13:30 – 13:50 Probabilistic Topic and Role Model for Information Diffusion in Social Network
Hengpeng Xu*, Nankai University; Jinmao Wei, Nankai University; Zhenglu Yang, Nankai University; Jianhua Ruan, University of Texas at San Antonio; Jun Wang, Nankai university
13:50 – 14:10 Topic-sensitive Influential Paper Discovery in Citation Network
Xin Huang, Shanghai Jiao Tong University; Chang-An Chen, Shanghai Jiao Tong University; Changhuan Peng, Shanghai Jiao Tong University; Xudong Wu, Shanghai Jiao Tong University; Luoyi Fu, Shanghai Jiao Tong University; Xinbing Wang*, Shanghai Jiao Tong University
14:10 – 14:30 Course-Specific Markovian Models for Grade Prediction
Qian Hu*, George Mason University; Huzefa Rangwala, George Mason University
14:30 – 14:50 A Temporal Topic Model For Noisy Mediums
Robert Churchill*, Georgetown University; Lisa Singh, Georgetown University; Christo Kirov, Georgetown University
14:50 – 15:10 A CRF-based Stacking Model with Meta-Features for Named Entity Recognition
Shifeng Liu*, University of New South Wales; Yifang Sun, University of New South Wales; Wei Wang, University of New South wales; Xiaoling Zhou, University of New South Wales
15:10 – 15:30 Adding Missing Words to Regular Expressions
Thomas Rebele*, Télécom ParisTech; Katerina Tzompanaki, Cergy-Pontoise University; Fabian Suchanek, Telecom ParisTech
Graphical models, latent variables and statistical methods (Part 2)
15:45 – 16:15 Marrying Community Discovery and Role Analysis in Social Media via Topic Modeling
Gianni Costa, ICAR-CNR; Riccardo Ortale*, ICAR-CNR
16:15 – 16:35 Text Generation Based on Generative Adversarial Nets with Latent Variables
heng wang, Beihang University; Zengchang Qin*, Beihang University; Tao Wan, Beihang University
16:35 – 16:55 Geminio: Finding Duplicates in a Question Haystack
sandya mannarswamy*, Conduent Labs ; saravanan chidambaram, HPE
16:55 – 17:15 Fast Converging Multi-armed Bandit Optimization using Probabilistic Graphical Model
Chen Zhao*, Graduate School of Systems and Information Engineering, University of Tsukuba; Kohei Watanabe, Graduate School of Information Science and Technology, University of Tokyo; Bin Yang, Rakuten; Yu Hirate, Rakuten Institute of Technology
17:15 – 17:35 Leveraging Label Category Relationships in Multi-class Crowdsourcing
YUAN JIN*, Monash University; Lan Du, Monash University; Ye Zhu, Deakin University; Mark Carman, Monash University
17:35 – 17:55 Embedding Knowledge Graphs Based on Transitivity and Asymmetry of Rules
Mengya Wang*, Sun Yat-sen University; Erhu Rong, Sun Yat-sen University; Hankui Zhuo, Sun Yat-sen University; Huiling Zhu, Sun Yat-sen University
Representation Learning and Embedding (Part 1)
10:15 – 10:45 SIGNet: Scalable Embeddings for Signed Networks
Mohammad Islam*, Virginia Tech; B. Aditya Prakash, Virginia Tech; Naren Ramakrishnan, Virginia Tech
10:45 – 11:15 Sub2Vec: Feature Learning for Subgraphs
Bijaya Adhikari*, Virginia Tech; Yao Zhang, Virginia Tech; Naren Ramakrishnan, Virginia Tech; B. Aditya Prakash, Virginia Tech
11:15 – 11:45 Interaction Content Aware Network Embedding via Co-embedding of Nodes and Edges
Linchuan Xu*, The Hong Kong Polytechnic University; Xiaokai Wei, Facebook Inc.; Jiannong Cao, The Hong Kong Polytechnic University; Philip S Yu, UIC
11:45 – 12:15 MetaGraph2Vec: Complex Semantic Path Augmented Heterogeneous Network Embedding
Daokun Zhang*, University of Technology Sydney; Jie Yin, The University of Sydney; Xingquan Zhu, Florida Atlantic University; Chengqi Zhang, University of Technology Sydney
Representation Learning and Embedding (Part 2)
13:30 – 14:00 Multi-Network User Identification via Graph-Aware Embedding
Yang Yang, Nanjing University; Yi-Feng Wu, Nanjing University; De-Chuan Zhan*, Nanjing University; Yuan Jiang, Nanjing University
14:00 – 14:30 Knowledge-based Recommendation with Hierarchical Collaborative Embedding
Zili Zhou, University of Technology Sydney; Shaowu Liu, University of Technology Sydney; Guandong Xu*, University of Technology Sydney, Australia; Xing Xie, Microsoft Research Asia; Jun Yin, University of Technology Sydney; Yidong Li, Beijing Jiaotong Univeristy, China; Wu Zhang, Shanghai University
14:30 – 14:50 DPNE: Differentially Private Network Embedding
Depeng Xu, University of Arkansas; Shuhan Yuan, University of Arkansas; Xintao Wu*, University of Arkansas; Hai Phan, New Jersey Institute of Technology
14:50 – 15:10 A Generalization of Recurrent Neural Networks for Graph Embedding
Xiao Han*, Beijing University of Posts and Telecommunications; Chunhong Zhang, Beijing University of Posts and Telecommunications; Chenchen Guo, Beijing University of Posts and Telecommunications; Yang Ji, Beijing University of Posts and Telecommunications
15:10 – 15:30 NE-FLGC: Network Embedding based on Fusing Local (first-order) and Global (second-order) network structure with node Content
Hongyan Xu*, TianJin University
Semi-Structured Data and NLP (Part 1)
10:15 – 10:45 Category Multi-Representation: A Unified Solution for Named Entity Recognition in Clinical Texts
Jiangtao Zhang*, Tsinghua University; Juanzi Li, Tsinghua University; Shuai Wang, Tsinghua University; Yan Zhang, Tsinghua University; Yixin Cao, Tsinghua University; Lei Hou, Tsinghua University; Xiaoli Li, Institute for Infocomm Research , A*STAR, Singapore
10:45 – 11:15 A Heterogeneous Information Network Method for Entity Set Expansion in Knowledge Graph
Xiaohuan Cao, Beijing University of Posts and Telecommunications; Chuan Shi*, Beijing University of Posts and Telecommunications; Yuyan Zheng, Beijing University of Posts and Telecommunications; Jiayu Ding, Beijing University of Posts and Telecommunications; Xiaoli Li, Institute for Infocomm Research , A*STAR, Singapore; Bin Wu, Beijing University of Posts and Telecommunications
11:15 – 11:35 Identifying In-App User Actions from Mobile Web Logs
Bilih Priyogi*, RMIT University; Mark Sanderson, RMIT University; Flora Salim, RMIT University; Jeffrey Chan, RMIT University, Australia; Martin Tomko, University of Melbourne; Yongli Ren, RMIT University
11:35 – 11:55 Harvesting Knowledge from Cultural Heritage Artifacts in Museums of India
Abhilasha Sancheti, Adobe Research; Paridhi Maheshwari, Indian Institute of Technology Kanpur; Rajat Chaturvedi, Indian Institute of Technology Bombay; Anish Monsy, Indian Institute of Technology Guwahati; Tanya Goyal, University of Texas at Austin; Balaji Vasan Srinivasan*, Adobe Research
11:55 – 12:15 Query-based Automatic Training Set Selection for Microblog Retrieval
khaled Albishre*, QUT; Yuefeng Li, Queensland University of Technology; Yue Xu, Queensland University of Technology, Australia
Semi-Structured Data and NLP (Part 2)
13:30 – 14:00 Distributed representation of multi-sense words: A loss driven approach
Saurav Manchanda*, University of Minnesota, Twin Cities; George Karypis, University of Minnesota, Twin Cities
14:00 – 14:30 Active Blocking Scheme Learning for Entity Resolution
Jingyu Shao*, ANU; Qing Wang, ANU
14:30 – 14:50 Mining Relations from Unstructured Content
Ismini Lourentzou, University of Illinois at Urbana – Champaign; Alfredo Alba, IBM Research; Anni Coden, IBM Research; Anna Lisa Gentile*, IBM Research; Daniel Gruhl, IBM Research; Steve Welch, IBM Research
14:50 – 15:10 Incorporating Word Embeddings into Open Directory Project based Large-scale Classification
Kang-Min Kim, Korea University; Dinara Aliyeva, Korea University; Byung-Ju Choi, Korea University; Sangkeun Lee*, Korea University,Korea
15:10 – 15:30 Inference of a Concise Regular Expression Considering Interleaving from XML Documents
Xiaolan Zhang*, State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences; Yeting Li, State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences; Fanlin Cui, State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences; Chunmei Dong, State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences and University of Chinese Academy of Sciences; Haiming Chen, State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences
Spatial-Temporal, Time-series and Stream Mining (Part 1)
10:15 – 10:45 Accelerating Adaptive Online Learning by Matrix Approximation
Yuanyu Wan*, Nanjing University; Lijun Zhang, Nanjing University
10:45 – 11:15 Cruising or Waiting: A Shared Recommender System for Taxi Drivers
Xiaoting Jiang*, Shanghai Jiao Tong University; Yanyan Shen, Shanghai Jiao Tong University; Yanmin Zhu, Shanghai Jiao Tong University
11:15 – 11:45 A Local Online Learning Approach for Non-linear Data
Xinxing Yang*, Ant Financial Services Group; Jun Zhou, Ant Financial; PEILIN ZHAO, Ant Finance Groups; Cen Chen, Ant Financial Services Group; Chaochao Chen, Ant Financial; Xiaolong Li, Ant Financial
11:45 – 12:15 Contextual Location Imputation for Confined WiFi Trajectories
Elham Naghizade*, The University of Melbourne; Jeffrey Chan, RMIT University, Australia; Yongli Ren, RMIT University; Martin Tomko, The University of Melbourne
Spatial-Temporal, Time-series and Stream Mining (Part 2)
13:30 – 14:00 Low redundancy estimation of correlation matrices for time series using triangular bounds
Erik Scharwächter*, Hasso Plattner Institute; Fabian Geier, HPI; Lukas Faber, Hasso Plattner Institute; Emmanuel Müller, Hasso Plattner Institute
14:00 – 14:30 Traffic Accident Detection with Spatiotemporal Impact Measurement
Mingxuan Yue*, University of Southern California; Liyue Fan, University at Albany SUNY; Cyrus Shahabi, Computer Science Department. University of Southern California
14:30 – 14:50 MicroGRID: An Accurate and Efficient Real-Time Stream Data Clustering With Noise
Zahir Tari*, RMIT University
14:50 – 15:10 UFSSF – An Efficient Unsupervised Feature Selection for Streaming Features
Naif Almusallam*, RMIT; Zahir Tari, RMIT University; Jeffrey Chan, RMIT University, Australia; Adil Alharthi, Albaha University
15:10 – 15:30 Online Clustering for Evolving Data Streams with Online Anomaly Detection
Milad Chenaghlou*, The University of Melbourne; Masud Moshtaghi, University of Melbourne; Christopher Leckie, University of Melbourne; Mahsa Salehi, Monash
Spatial-Temporal, Time-series and Stream Mining (Part 3)
16:00 – 16:20 An Incremental Dual nu-Support Vector Regression Algorithm
Hang Yu*, University of Technology Sydney; Jie Lu, University of Technology Sydney; Guangquan Zhang, University of Technology Sydney
16:20 – 16:40 Text Stream to Temporal Network – A Dynamic Heartbeat Graph to Detect Emerging Events on Twitter
Zafar Saeed, Quaid i Azam University; Rabeeh Abbasi, Quaiz Azam University; Abida Sadaf, Quaid i Azam University; Imran Razzak, KSAU-HS; Guandong Xu*, University of Technology Sydney, Australia
16:40 – 17:00 Model the Dynamic Evolution of Facial Expression from Image Sequences
Zhaoxin Huan*, Nanjing university; Lin Shang, Nanjing University
17:00 – 17:20 Unsupervised Disaggregation of Low Granularity Resource Consumption Time Series
Pantelis Chronis*, University of Peloponnese; Spiros Skiadopoulos, University of Peloponnese; Giorgos Giannopoulos, Athena RC
17:20 – 17:40 STARS: Soft Multi-Task Learning for Activity Recognition from Multi-Modal Sensor Data
Xi Liu*, Michigan State University; Pang-Ning Tan, MSU; Lei Liu, HP Labs
17:40 – 18:00 A refined MISD algorithm based on Gaussian process regression
Feng Zhou*, Data61; Zhidong Li, Data61, CSIRO; Xuhui Fan, UNSW; Yang Wang, Data61, CSIRO; Arcot Sowmya, UNSW; Fang Chen, CSIRO
Feature Learning and Data Mining Process (Part 1)
10:15 – 10:45 Discovering High Utility Itemsets Based on the Artificial Bee Colony Algorithm
Wei Song*, North China University of Technology; Chaomin Huang, North China University of Technology
10:45 – 11:05 A Scalable and Efficient Subgroup Blocking Scheme for Multidatabase Record Linkage
Thilina Ranbaduge*, The Australian National University; Dinusha Vatsalan, Australian National University; Peter Christen, The Australian National University
11:05 – 11:25 Efficient Feature Selection Framework For Digital Marketing Applications
Wei Zhang*, Adobe; shiladitya bose, Adobe; Said Kobeissi, Adobe; Scott Tomko, Adobe; Chris Challis, adobe
11:25 – 11:45 Dynamic feature selection algorithm based on minimum vertex cover of hypergraph
Xiaojun Xie, College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics; Xiaolin Qin*, College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics
11:45 – 12:05 Feature Selection for Multiclass Binary Data
Kushani Perera*, University of Melbourne
Feature Learning and Data Mining Process (Part 2)
13:30 – 14:00 Scalable Model-based Cascaded Imputation of Missing Data
Jacob Montiel*, Télécom ParisTech, Université Paris-Saclay; Jesse Read, Ecole Polytechnique; Albert Bifet, Telecom ParisTech; Talel Abdessalem, Telecom ParisTech
14:00 – 14:30 On Reducing Dimensionality of Labeled Data Efficiently
Guoxi Zhang*, Kyoto University; Tomoharu Iwata, NTT Communication Science Laboratories; Hisashi Kashima, Kyoto University
14:30 – 14:50 Using Metric Space Indexing for Complete and Efficient Record Linkage
Özgür Akgün*, University of St Andrews; Alan Dearle, University of St Andrews; Graham Kirby, University of St Andrews; Peter Christen, The Australian National University
14:50 – 15:20 Dimensionality Reduction via Community Detection in Small Sample Datasets
Kartikeya Bhardwaj*, Carnegie Mellon University; Radu Marculescu, Carnegie Mellon University
15:20 – 15:50 An interaction-enhanced feature selection algorithm
Xiaochuan Tang*, University of Electronic Science and Technology of China; Yuanshun Dai, University of Electronic Science and Technology of China; Yanping Xiang, University of Electronic Science and Technology of China; Liang Luo, University of Electronic Science and Technology of China
Feature Learning and Data Mining Process (Part 3)
16:00 – 16:30 An Extended Random-Sets Model for Fusion-based Text Feature Selection
Abdullah Alharbi*, QUT; Yuefeng Li, Queensland University of Technology; Yue Xu, Queensland University of Technology, Australia
16:30 – 16:50 Attribute Reduction Based on Improved Information Gain Rate and Ant Colony Optimization
Wei Jipeng*, Guilin University of Electronic Technology; Wen Yimin, Guilin University of Electronic Technology; Wei Qianjin, Guilin University of Electronic Technology
16:50 – 17:10 Efficient Approximate Algorithms for the Closest Pair Problem in High Dimensional Spaces
Xingyu Cai, University of Connecticut; Sanguthevar Rajasekaran*, University of Connecticut; Fan Zhang, Zhejiang University
17:10 – 17:30 Efficient Compression Technique for Sparse Sets
rameshwar Pratap*, CMI; Ishan Sohony, Pune Institute of Computer Technology, Pune; Raghav Kulkarni, CMI
17:30 – 17:50 It pays to be Certain: Unsupervised Record Linkage via Ambiguity Minimization
Anna Jurek*, Queen’s University; Deepak P, Queen’s University Belfast
Community Detection and Network Science
16:00 – 16:30 Consensus Community Detection in Multilayer Networks using Parameter-free Graph Pruning
Domenico Mandaglio, DIMES, University of Calabria; Alessia Amelio, DIMES, University of Calabria; Andrea Tagarelli*, DIMES, University of Calabria, IT
16:30 – 17:00 Community Discovery Based on Social Relations and Temporal-Spatial Topics in LBSNs
Shuai Xu, Southeast University; Jiuxin Cao*, Southeast University; Xuelin Zhu, Southeast University; Yi Dong, Southeast University; Bo Liu, Southeast University
17:00 – 17:20 A Unified Weakly Supervised Framework for Community Detection and Semantic Matching
Xiao Liu*, Tianjin University; di jin, School of Computer Software, Tianjin University
17:20 – 17:50 Tapping Community Memberships and Devising a Novel Homophily Modeling Approach for Trust Prediction
Pulkit Parikh*, IIIT Hyderabad; Manish Gupta, Microsoft; Vasudeva Varma, IIIT Hyderabad
Deep Learning Theory and Applications in KDD (Part 1)
10:15 – 10:45 Text-visualizing Neural Network Model: Understanding Online Financial Textual Data
Tomoki Ito*, The University of Tokyo; Hiroki Sakaji, The University of Tokyo; Kota Tsubouchi, Yahoo Japan Corporation; 潔 和泉, 東京大学; Tatsuo Yamashita, Yahoo Japan Corporation
10:45 – 11:05 MIDA: Multiple Imputation using Denoising Autoencoders
lovedeep gondara*, simon fraser university; Ke Wang, SFU
11:05 – 11:25 Dual Control Memory Augmented Neural Networks for Treatment Recommendations
Hung Le*, Deakin University; Truyen Tran, Deakin University; Svetha Venkatesh, Deakin University
11:25 – 11:45 Denoising Time Series Data Using Asymmetric Generative Adversarial Networks
Sunil Gandhi*, University Of Maryland Baltimore County; Tim Oates, University Of Maryland Baltimore County; Tinoosh Mohsenin, Nil; David Hairston, Nil
11:45 – 12:15 Shared Deep Kernel Learning for Dimensionality Reduction
Xinwei Jiang*, China University of Geosciences; Junbin Gao, University of Sydney, Australia; Xiaobo Liu, China University of Geosciences; Zhihua Cai, China University of Geosciences; Dongmei Zhang, China University of Geosciences; Yuanxing Liu, China University of Geosciences
Deep Learning Theory and Applications in KDD (Part 2)
14:45 – 15:05 CDSSD: Refreshing Single Shot Object Detection Using A Conv-Deconv Network
Vijay Gabale*, Huew; Uma Sawant, IIT Bombay
15:05 – 15:25 Binary Classification of Sequences Possessing Unilateral Common Factor with AMS and APR
Yujin Tang*, KDDI Research, Inc.; Kei Yonekawa, KDDI Research, Inc.; Mori Kurokawa, KDDI Research, Inc.; Shinya Wada, KDDI Research, Inc.; Kiyohito Yoshihara, KDDI Research, Inc.
15:25 – 15:45 Automating reading comprehension by generating question and answer pairs
Vishwajeet Kumar*, IITB-Monash Research Academy; kireeti Boorla, Oracle; Yogesh Meena, IIT Bombay; Ganesh Ramkrishnan, IIT Bombay; Yuan-Fang Li , Monash University
15:45 – 16:05 Emotion Classification with Data Augmentation Using Generative Adversarial Networks
Xinyue Zhu*, BUPT; Yifan Liu, Beihang University; Jiahong Li, Beijing San Kuai Yun Technology Co., Ltd; Tao Wan, Beihang University; Zengchang Qin, Beihang University
16:05 – 16:25 Trans2Vec: Learning Transaction Embedding via Items and Frequent Itemsets
Dang Nguyen*, Deakin University; Tu Nguyen, “Deakin University, Australia”; Wei Luo, Deakin University; Svetha Venkatesh, Deakin University
16:25 – 16:45 Detecting Complex Sensitive Information via Phrase Structure in Recursive Neural Networks
Jan Neerbek*, University of Aarhus; Ira Assent, University of Aarhus; Peter Dolog, University of Aalborg
Clustering and Unsupervised Learning (Part 1)
10:15 – 10:45 A Distance Scaling Method to Improve Density-based Clustering
YE ZHU*, Deakin University; Kai Ming Ting, Federation University, Australia; Maia Angelova, Deakin University
10:45 – 11:15 Neighbourhood Contrast: A better means to detect clusters than density
Bo Chen*, Monash University; Kai Ming Ting, Federation University, Australia
11:15 – 11:35 Clustering of Multiple Density Peaks
borui cai*, deakin university; guangyan huang, deakin university; yong xiang, deakin university
11:35 – 11:55 A New Local Density for Density Peak Clustering
William Zhu*, University of Electronic Science and Technology of China
11:55 – 12:15 An Efficient Ranking-centered Density-based Document Clustering Method
Wathsala Mohotti*, QUT; Richi Nayak, Queensland University of Technology, Brisbane
Clustering and Unsupervised Learning (Part 2)
14:45 – 15:05 Fast Manifold Landmarking using Locality Sensitive Hashing
Zay Maung Maung Aye*, University of Melbourne; Kotagiri Ramamohanarao, The University of Melbourne; Benjamin Rubinstein, University of Melbourne
15:05 – 15:25 Equitable Conceptual Clustering using OWA operator
Noureddine Aribi, University of Oran; Abdelkader Ouali, University of Caen Normandy; Yahia Lebbah, University of Oran; Samir Loudni*, University of Caen Normandy
15:25 – 15:55 Unsupervised Extremely Randomized Trees
Kevin Dalleau*, LORIA; Malika Smail-Tabbone, LORIA; Miguel Couceiro, LORIA
15:55 – 16:25 Local Graph Clustering by Multi-network Random Walk with Restart
Yaowei Yan*, The Pennsylvania State University; Dongsheng Luo, The Pennsylvania State University; Jingchao Ni, The Pennsylvania State University; Hongliang Fei, Baidu Big Data Lab; Wei Fan, Baidu Big Data Lab; John Yen, The Pennsylvania State University; Xiong Yu, Case Western Reserve University; Xiang Zhang, The Pennsylvania State University
16:25 – 16:45 Scalable Approximation Algorithm for Graph Summarization
Maham Anwar Beg, Lahore University of Management Sciences; Muhammad Ahmad, Lahore University of Management Sciences; Arif Zaman, Lahore University of Management Sciences; Imdadullah Khan*, Lahore University of Management Sciences
Privacy-Preserving and Security
10:15 – 10:45 RIPEx: Extracting malicious IP addresses from security forums using cross-forum learning
Joobin Gharibshah*, University of California, Riverside; Evangelos Papalexakis, UC Riverside; Michlais Michail Faloutsos, University of California, Riverside
10:45 – 11:15 Pattern-Mining based Cryptanalysis of Bloom Filters for Privacy-Preserving Record Linkage
Peter Christen*, The Australian National University; Anushka Vidanage, The Australian National University; Thilina Ranbaduge, The Australian National University; Rainer Schnell, University Duisburg-Essen
11:15 – 11:45 A Privacy Preserving Bayesian Optimization with High Efficiency
Thanh Dai Nguyen*, Deakin University; Sunil Gupta, Deakin University, Australia; Santu Rana, Deakin University, Australia; Svetha Venkatesh, Deakin University
11:45 – 12:15 Randomizing SVM against Adversarial Attacks Under Uncertainty
Yan Chen, Columbia University; Wei Wang, Beijing Jiaotong University; Xiangliang Zhang*, ” King Abdullah University of Science and Technology, Saudi Arabia”
Recommendation and Data Factorization
14:45 – 15:05 One for the Road: Recommending Male Street Attire
Debopriyo Banerjee*, IIT Kharagpur; Niloy Ganguly, IIT Kharagpur; Krothapalli Sreenivasa Rao, IIT Kharagpur; Shamik Sural, Indian Institute of Technology Kharagpur
15:05 – 15:35 Context-aware Location Annotation on Mobility Records through User Grouping
Yong Zhang, Beihang University; Hua Wei, Pennsylvania State University; Xuelian Lin*, Beihang University; Fei Wu, Pennsylvania State University; Zhenhui (Jessie) Li, Penn State University; Kaiheng Chen, Beihang University; Yuandong Wang, Beihang University; Jie Xu, University of Leeds
15:35 – 16:05 A Joint Optimization Method for Personalized Recommendation Result Diversification
Xiaojie Wang*, The University of Melbourne; Jianzhong Qi, The University of Melbourne; Kotagiri Ramamohanarao, The University of Melbourne; Yu Sun, University of Melbourne; Bo Li, University of Illinois at Urbana–Champaign; Rui Zhang, ” University of Melbourne, Australia”
16:05 – 16:35 Personalized Item-of-Interest Recommendation on Storage Constrained Smartphone based on Word Embedding Quantization
Si-Ying Huang, National Chung Hsing University; Yung-Yu Chen, National Center for High-Performance Computing; Hung-Yuan Chen, ITRI; Chen Lun-Chi, National Center for High-Performance Computing; Yao-Chung Fan*, National Chung Hsing Universit
Social Network, Ubiquitous Data and Graph Mining (Part 1)
16:00 – 16:30 Topic-specific Retweet Count Ranking for Weibo
Hangyu Mao*, Peking University; Yang Xiao, Peking University; Yuan Wang, Peking University; Jiakang Wang, Peking University; Zhen Xiao, Peking University
16:30 – 17:00 Motif-Aware Diffusion Networks Inference
Qi Tan, HKBU; Yang Liu, Hong Kong Baptist University; Jiming Liu*, Hong Kong Baptist University
17:00 – 17:20 Tri-Fly: Distributed Estimation of Global and Local Triangle Counts in Graph Streams
Kijung Shin*, Carnegie Mellon University; Mohammad Hammoud, Carnegie Mellon University; Euiwoong Lee, Carnegie Mellon University; Jinoh Oh, Adobe Systems; Christos Faloutsos, CMU, Pittsburgh
17:20 – 17:40 WFSM-MaxPWS: An Efficient Approach for Mining Weighted Frequent Subgraphs from Edge-Weighted Graph Databases
Md. Ashraful Islam, University of Dhaka; Chowdhury Farhan Ahmed, University of Dhaka; Carson Leung*, University of Manitoba; Calvin Hoi, University of Manitoba
17:40 – 18:00 A Game-Theoretic Adversarial Approach to Dynamic Network Prediction
Jia Li*, University of Illinois at Chicago; Brian Ziebart, UIC; Tanya Berger-Wolf, University of Illinois
Social Network, Ubiquitous Data and Graph Mining (Part 2)
10:15 – 10:45 Targeted Influence Minimization in Social Networks
Xinjue Wang, RMIT; Ke Deng*, RMIT University; Jianxin Li, The University of Western Australia; Xiaochun Yang, Northeast University; Jeffrey Xu Yu, Chinese University of Hong Kong, Hong Kong; Christian Jensen, Aalborg University
10:45 – 11:15 Maximizing Social Influence on Target Users
Yu-Ting Wen*, National Chiao Tung University; Wen-Chih Peng, National Chiao Tung University, Taiwan; Hong-Han Shuai, National Chiao Tung University
11:15 – 11:35 Team Expansion in Collaborative Environments
Lun Zhao*, Nanjing University; Yuan Yao, Nanjing University; Guibing Guo, Northeastern University; Hanghang Tong, Arizona State University; Feng Xu, Nanjing University; Jian Lv, Nanjing University
11:35 – 11:55 HashAlign: Hash-based Alignment of Multiple Graphs
Wei Lee, University of Michigan; Mark Heimann*, University of Michigan; Shengjie Pan, University of Michigan; Kuan-yu Chen, University of Michigan; Danai Koutra, U Michigan
11:55 – 12:15 Evaluating and Analyzing Reliability over Decentralized and Complex Networks
Jaron Mar, University of Auckland; Jiamou Liu*, University of Auckland; Yanni Tang, College of Computer & Information Science, Southwest University; Wu Chen, College of Computer & Information Science, Southwest University; Tianyi Sun, University of Auckland
Social Network, Ubiquitous Data and Graph Mining (Part 3)
14:45 – 15:05 Efficient Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs
Mostafa Haghir Chehreghani*, Telecom Paristech; Albert Bifet, Telecom ParisTech; Talel Abdessalem, Telecom ParisTech
15:05 – 15:25 Forecasting Bitcoin Price with Graph Chainlets
Cuneyt Akcora*, University of Texas at Dallas; Yulia Gel, The University of Texas at Dallas; Murat Kantarcioglu, UT Dallas; Asim Dey, University of Texas at Dallas
15:25 – 15:45 Information Propagation Trees for Protest Event Prediction
JEFFERY ANSAH*, University of South Australia, UniSA, Data Analytics Group; Wei Kang, University of South Australia; Lin Liu, University of South Australia; Jixue Liu, University of South Australia; Jiuyong Li, University of South Australia
15:45 – 16:05 Predictive Social Team Formation Analysis via Feature Representation Learning
Lo-Pang-Yun Ting, National Cheng Kung University; Cheng-Te Li, National Cheng Kung University; Kun-Ta Chuang*, National Cheng Kung University
16:05 – 16:25 Leveraging Local Interactions for Geolocating Social Media Users
Mohammad Ebrahimi*, University of New South Wales; Elaheh ShafieiBavani, University of New South Wales; Raymond Wong, University of New South Wales; Fang Chen, University of New South Wales
16:25 – 16:45 Utilizing sequences of touch gestures for user verification on mobile devices
Liron Ben Kimon*, Ben Gurion University; Yisroel Mirsky, Ben Gurion University; Lior Rokach, Ben Gurion University; Bracha Shapira, Ben-Gurion University of the Negev