CFP: AusDM 2016. Submission due 19 Aug

posted Apr 28, 2016, 7:19 AM by Yanchang Zhao   [ updated Apr 28, 2016, 7:21 AM ]

14th Australasian Data Mining Conference (AusDM 2016)
Canberra, Australia,
6-8 December 2016
Join us on LinkedIn:

The Australasian Data Mining Conference has established itself as the premier Australasian meeting for both practitioners and researchers in data mining. AusDM'16 seeks to showcase: Research Prototypes; Industry Case Studies; Practical Analytics Technology; and Research Student Projects.

Publication and topics
We are calling for papers, both research and applications, and from both academia and industry, for presentation at the conference. Accepted papers will be published in an up-coming volume (Data Mining and Analytics 2016) of the Conferences in Research and Practice in Information Technology (CRPIT) series by the Australian Computer Society which is also held in full-text on the ACM Digital Library. AusDM invites contributions addressing current research in data mining and knowledge discovery as well as experiences, novel applications and future challenges.

Submission of papers
- Academic submissions: Regular academic submissions can be made in Research Track reporting on research progress, with a paper length of between 8 and 12 pages in CRPIT style.
- Industry submissions: Submissions can be made in the Application Track to report on specific data mining implementations and experiences in governments and industry projects. Submissions in this category can be between 4 and 8 pages in CRPIT style.
- Industry Showcase submissions: Submission from industry and government on an analytics solution that has raised profits, reduced costs and/or achieved other important policy and/or business outcomes can be made in this track with a one page Abstract only.

Important Dates
Paper Submission Closed: Friday 19 August 2016
Authors Notified: Monday 24 October 2016
Camera Ready Submission: Monday 7 November 2016
Conference Dates: 6-8 December 2016

Upcoming Training

posted Apr 24, 2016, 3:01 PM by Yanchang Zhao   [ updated Apr 24, 2016, 3:02 PM ]

I will run one-week training for the Big Data and Analytics course at the S P Jain School of Global Management, Mumbai, India, 30 May - 5 June 2016.

Hadoop, Spark, NoSQL and Data Science Training Courses with exclusive 15% discount

posted Apr 6, 2016, 3:53 AM by Yanchang Zhao   [ updated Apr 6, 2016, 3:53 AM ]

DeZyre provides webinar and training courses on big data and data science as below. Enrol at the links below to get an exclusive 15% discount.

Twitter Data Analysis with R

posted Feb 15, 2016, 1:22 AM by Yanchang Zhao   [ updated Feb 15, 2016, 1:24 AM ]

Slides of my invited talk on Twitter Data Analysis with R at the Making Data Analysis Easier Workshop Organised by the Monash Business Analytics Team (WOMBAT 2016) are available as file RDataMining-slides-twitter-analysis.pdf at the Documents page.


A Twitter dataset for text mining

posted Feb 9, 2016, 4:22 AM by Yanchang Zhao   [ updated Feb 9, 2016, 4:23 AM ]

A dataset of @RDataMining Tweets extracted on 3 February 2016 is now available at Datasets. The dataset can be used for text mining purpose.

Seminar on Cyberbullying Detection by Applying AI Approaches, University of Canberra, 4:30pm Tuesday 2 Feb 2016

posted Jan 27, 2016, 12:39 AM by Yanchang Zhao   [ updated Jan 27, 2016, 12:39 AM ]

Topic: Cyberbullying Detection by Applying AI Approaches
Speakers: Prof. Chengqi Zhang and Dr. Guodong Long, University of Technology, Sydney
Organisers: The Canberra Data Scientists group and the Information Technology & Engineering Program, University of Canberra
Date and time: 4:30-6:00pm, Tuesday, 2 February 2016
Location: Teal Room, Inspire Centre (Building 25 on the map at

Cyberbullying is the use of technology to bully a person or group with the intent to hurt them socially, psychologically or even physically.  Currently there are many young people being cyberbullied or involving in cyberbullying activities, and the cyberbullying offence has been defined as criminal activity by law. To avoid the severe results (e.g. spirit trauma, or be charged as criminal), cyberbullying detection emerged to real-time proactively prevent cyberbullying by generating early warning. Most studies on Cyberbullying detection focus on key-words search and sentiment filtering on textual contents. All of them neglects the online conversation's rich context information including texts, networks, time and demographics. In this talk, we will introduce a novel solution for applying AI approaches to detect cyberbullying by exploiting rich heterogeneous context information.

Prof. Chengqi Zhang is a Research Professor of Information Technology at The University of Technology Sydney (UTS), an Honorary Professor of the University of Queensland (UQ), Director of the UTS Priority Research Centre for Quantum Computation & Intelligent Systems (QCIS). He is Alternative Dean of UTS Graduate Research School, Chairman of the Australian Computer Society National Committee for Artificial Intelligence and Chairman of IEEE Computer Society Technical Committee of Intelligent Informatics (TCII). Chengqi Zhang obtained his PhD degree from the University of Queensland in 1991, followed by a Doctor of Science (DSc – Higher Doctorate) from Deakin University in 2002. His key areas of research are Distributed Artificial Intelligence, Data Mining and its applications. He has published more than 200 refereed research papers and six monographs and edited 16 books. He has attracted 12 ARC grants of $4.7M. He is a Fellow of the Australian Computer Society (ACS) and a Senior Member of the IEEE Computer Society (IEEE).

Dr. Guodong Long has over 10 years experience on leading, developing and coordinating industry and research projects. Since joined UTS in 2010, he has practically led total five industry projects including three ARC Linkage projects. Before join in UTS in 2010, Dr Long has over 6 years industry work experience in IT company. He has strong system-wide knowledge of all computer-related, especially for architecture and design for artificial intelligent based systems; and have strong creativity on research methodology and real application systems. He currently leads a research team to conduct application-driven research by collaborating with industry partners. He obtained his BSc and MSc degree from National University of Defence Technology (NUDT) in 2002, 2008, and PhD degree from University of Technology Sydney (UTS) in 2014, all from computer science.

Slides of 10+ excellent tutorials at KDD 2015: Spark, graph mining and many more

posted Aug 17, 2015, 4:01 AM by Yanchang Zhao   [ updated Aug 17, 2015, 4:02 AM ]

See slides of 10+ excellent tutorials at KDD 2015 at, incl.
  • VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms
  • Graph-Based User Behavior Modeling: From Prediction to Fraud Detection
  • A New Look at the System, Algorithm and Theory Foundations of Large-Scale Distributed Machine Learning
  • Dense subgraph discovery (DSD)
  • Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach
  • Big Data Analytics: Optimization and Randomization
  • Big Data Analytics: Social Media Anomaly Detection: Challenges and Solutions
  • Diffusion in Social and Information Networks: Problems, Models and Machine Learning Methods
  • Medical Mining
  • Large Scale Distributed Data Science using Apache Spark
  • Data-Driven Product Innovation
  • Web Personalization and Recommender Systems a mirror site for Chinese users

posted Aug 5, 2015, 5:30 AM by Yanchang Zhao   [ updated Aug 5, 2015, 5:31 AM ] now has a mirror website at Users in China can download RDataMining documents, code and data at above mirror site, if no access to

Note that will still be the primary site and please visit only when you have no access to the primary site.

Please let me know if you have access to neither of two sites below. Thanks.

CIKM Machine Learning Competition 2015

posted Jul 28, 2015, 12:29 PM by Yanchang Zhao   [ updated Jul 28, 2015, 12:29 PM ]

The CIKM Machine Learning Competition 2015 is centered around the AFL. Participants are required to predict the outcomes of every match in the 2015 AFL season in two phases:

- the Leaderboard phase, where contestants predict the outcome of each regular-season match in the 2015 AFL season. The corresponding leaderboard will be updated as the season progresses. This phase will be based on an honour system since the results of matches will already be known.

- the Finals phase, where contestants predict the outcome of each match in the 2015 AFL Finals Series. Submissions will close prior to the commencement of the first finals series match. The final leaderboard of the competition will be determined from these matches and a competition winner will be annonced after the 2015 AFL Grand Final.

The winner of the competition will be awarded $5,000 (AUD) and will be required to provide a satisfactory description of their approach.

Competition opens: 24 July 2015
Submissions close: 10 Sept 2015


The 2015 Big Data Summit, 9-10 August 2015, collocated with ACM KDD 2015, Sydney

posted Jul 14, 2015, 1:31 PM by Yanchang Zhao

The 2015 Big Data Summit
9-10 August 2015
collocated with ACM KDD 2015, Sydney

We take this privilege opportunity to invite you to
participate in the 2015 Big Data Summit:
• Co-located with ACM KDD2015
• Plenary sessions and keynote speeches by world
industrial and academic leaders
• Big data best practices and highlights in Australia
and New Zealand
• “Big Data in China” Forum
• “Data Science in India” Forum
• “Big Data in Asia” Panel

The theme of this year’s Big Data Summit is “Data to

Since the Summit’s inception in 2012, we have seen
increasing interest and investment within both
industry and government in data-led innovation and
industralisation to deeply explore big data universe,
invent data science, train data engineers and scientists,
and develop the data economy.

This year’s event aims to provide analytics professionals
and academia with a global and regional perspective to
outline the big data research, education and development
in the Asia Pacific region, showcase best practices,
explore thought-provoking insights, and demonstrate
solutions and lessons learned across industry,
government and academia.

Who Should Attend?
• Data modellers and business analysts
• Analytics professionals
• Business decision makers
• Policy executives
• Senior Government Representatives
• Academics (including research students)

What Are the Trends and Topics?
• The Data2Economy Agenda: Challenges, Trends and
• Latest Scientific Development in Data and Analytics
• The progress and future of big data in Australia and
New Zealand
• The progress and future of big data in China
• The progress and future of data science in India
• Future of Data Science and Analytics Science
• Data Economy and Industrial Transformation
• Competency, Policies and Processes
• Data Analytics Case Studies and Showcases

Why You Should Attend?
Started in 2012, the 2013 and 2014 Big Data Summit
(Sydney and Canberra) attracted over 250-300
participants from industry, government and academia.
This annual Australian Summit provides a premier and
unique forum for bridging the gaps between academia,
industry and government, and independent insights on the
advancement, best practices, trends and controversies
about data science, big data and data economy.

With very prestigious speakers across academic, industry
and government from China, India, Australia, and USA
and Europe, the 2015 Summit will cover a broad spectrum
of big data and analytics aspects and domains. The three
regional Forums organized by India, China and ANZ will
present first-hand view about progress and opportunities
in the Asia Pacific region. The “Big Data in Asia” Panel
will feature world leaders from both the Asia Pacific and
global communities, to draw a big picture of big data
innovation, services, education and economy.

Co-located with ACM KDD2015 in Hilton Sydney, BDS2015
attracts global interest, will mark a unique and high
quality opportunity for you and your organization to grasp
the cutting-edge and thought-leading progress, network
with peers and thought leaders, and most importantly,
dig out more insights and value from your big data and
lift your competency in the increasingly competitive and
challenging market and environment.

For More Information
For more details about the Summit, please visit the Website

Registration to BDS2015 will be free of charge, please Check
and Register via

For any other inquiries about the Summit, please feel free to
Contact us(

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