Topics of Interest -- Research Track

General areas of interest to DSAA'2016 include but are not limited to: 

• Foundations

• New mathematical, probabilistic and statistical models and theories

• New machine learning theories, models and systems

• New knowledge discovery theories, models and systems

• Manifold and metric learning, deep learning

• Scalable analysis and learning

• Non-iidness learning

• Heterogeneous data/information integration

• Data pre-processing, sampling and reduction

• High dimensional data, feature selection and feature transformation

• Large scale optimization

• High performance computing for data analytics

• Architecture, management and process for data science

• Data analytics, machine learning and knowledge discovery

• Learning for streaming data

• Learning for structured and relational data

• Intent and insight learning

• Mining multi-source and mixed-source information

• Mixed-type and structure data analytics

• Cross-media data analytics

• Big data visualization, modeling and analytics

• Multimedia/stream/text/visual analytics

• Relation, coupling, link and graph mining

• Personalization analytics and learning

• Web/online/social/network mining and learning

• Structure/group/community/network mining

• Cloud computing and service data analysis

• Storage, retrieval and search

• Data warehouses, cloud architectures

• Large-scale databases

• Information and knowledge retrieval, and semantic search

• Web/social/databases query and search

• Personalized search and recommendation

• Human-machine interaction and interfaces

• Crowdsourcing and collective intelligence

• Privacy and security

• Security, trust and risk in big data

• Data integrity, matching and sharing

• Privacy and protection standards and policies

• Privacy preserving big data access/analytics

• Social impact

• Topics of Interest -- Applications Track

• Papers in this track should motivate, describe and analyse the use Data Analytics tools and/or techniques in practical application as well as illustrate their actual impact. 

We seek contributions that address topics such as (but not limited to) the following: 

• Best practices and lessons

• Data-intensive organizations, business and economy

• Quality assessment and interestingness metrics

• Complexity, efficiency and scalability

• Big data representation and visualization

• Business intelligence, data-lakes, big-data technologies

• Large scale application case studies and domain-specific applications, such as but not limited to:

• Online/social/living/environment data analysis

• Mobile analytics for hand-held devices

• Anomaly/fraud/exception/change/event/crisis analysis

• Large-scale recommender and search systems

• Data analytics applications in cognitive systems, planning and decision support

• End-user analytics, data visualization, human-in-the-loop, prescriptive analytics

• Business/government analytics, such as for financial services, manufacturing, retail, utilities, telecom, national security, cyber-security, e-governance, etc.