PAISI – The 12th Pacific Asia Workshop on Intelligence and Security Informatics
– Michael Chau (The University of Hong Kong, China)
– G. Alan Wang (Virginia Tech, United States)
– Hsinchun Chen (The University of Arizona, United States)
Contact: mchau (at) business.hku.hk
Intelligence and Security Informatics (ISI) is concerned with the study of the development and use of advanced information technologies and systems for national, international, and societal security-related applications. The annual IEEE International Conference series on ISI was started in 2003. In 2006, the Workshop on ISI was started in Singapore in conjunction with PAKDD, with most contributors and participants from the Pacific Asian region. Since then, PAISI was held annually in Chengdu (2007), Taipei (2008), Bangkok (2009), Hyderabad (2010), Beijing (2011), Kuala Lumpur (2012), Beijing (2013), Tainan (2014), Ho Chi Minh City (2015), Auckland (2016) and Jeju, South Korea (2017). PAISI 2018 will be held in conjunction with PAKDD (http://prada-research.net/pakdd18/) and will provide a stimulating forum for ISI researchers in Pacific Asia and other regions of the world to exchange ideas and report research progress.
Selected PAISI 2018 papers will be published in Springer’s Lecture Notes in Artificial Intelligence (LNAI) series, which is indexed by EI Compendex, ISI Proceedings, and Scopus.
BDM – The 7th Workshop on Biologically-inspired Techniques for Knowledge Discovery and Data Mining
– Shafiq Alam (University of Auckland, New Zealand)
– Gillian Dobbie (University of Auckland, New Zealand)
Contact: shafiq (at) cs.auckland.ac.nz
For the last few years, biologically inspired data mining techniques have been intensively used in different data mining applications such as data clustering, classification, association rule mining, sequential pattern mining, outlier detection, feature selection and bioinformatics. The techniques include Neural Networks, Evolutionary Computation, Fuzzy Systems, Genetic Algorithms, Ant Colony Optimization, Particle Swarm Optimization, Artificial Immune Systems, Culture Algorithms, Social evolution, and Artificial Bee Colony Optimization. A huge increase in the number of papers published in the area has been observed in the last decade. Most of these techniques use optimization to speed up the data mining process and improve the quality of patterns mined from the data. The aim of the workshop is to highlight the current research related to biologically inspired techniques in different data mining domains and their implementation in real life data mining problems. The workshop will provide a platform to the researcher from computational intelligence and evolutionary computation and other biologically inspired techniques to get feedback on their work from other data mining perspective such as statistical data mining , AI and machine learning based data mining.
The workshop highlights a relatively new but fast growing area of data mining which is based on optimization techniques from biological behaviour of animals, insects, cultures, social behaviors and biological evolution. Techniques based on these models have been studied substantially, well optimized and tuned for different application areas in the previous decade. Knowledge Discovery and Data mining has been observed as one of the fastest growing application area of these nature inspired techniques.
BDASC – Big Data Analytics for Social Computing
– Mark Western (The University of Queensland, Australia)
– Junbin Gao (The University of Sydney, Australia)
– Lin Wu (The University of Queensland, Australia)
– Michele Haynes (Australian Catholic University, Australia)
– Yang Wang (Dalian University of Technology, China)
Contact: lin.wu (at) uq.edu.au
DaMEMO – Data Mining for Energy Modeling and Optimization
– Irena Koprinska (University of Sydney, Australia)
– Jeremiah Deng (University of Otago, New Zealand)
– Alicia Troncoso (University Pablo De Olavide, Spain)
Contact: irena.koprinska (at) sydney.edu.au
ML4Cyber – Australasian Workshop on Machine Learning for Cyber-security
– Jonathan Oliver (TrendMicro, Australia)
– Jun Zhang (Swinburne University of Technology, Australia)
Contact: Jon_oliver (at) trendmicro.com