ICDM 2012 provides a venue for high-quality workshops on a wide range of exciting topics.
|Permeke||Watteau I||Watteau II||Willumsen||Rembrandt||Horizon II (30th floor)||Holbein|
|Tintoretto I||Tintoretto II||Turner||Alto & Mezzo|
(ordered alphabetically on acronym)
Below you will find short descriptions per workshop. (more descriptions will follow)
Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data. To exploit these biomedical data for discovering new knowledge that can be translated into clinical applications, there are fundamental difficulties that have to be overcome. This workshop will disseminate the best data mining approaches to address the challenging issues in various biomedical data analysis.
Co-clustering is an important tool in a variety of scientific areas including document clustering, bioinformatics and information retrieval. Compared with the classical clustering algorithms, co-clustering algorithms have been shown to be more effective in discovering certain hidden clustering structures in data. This workshop intends to provide a forum for researchers in the field of Machine Learning, Statistics, Bioinformatics and Data Mining to discuss the above and other related topics regarding co-clustering and their applications.
This workshop aims to bring together researchers and practitioners interested in data mining algorithms that produce models that optimize income and take better account of costs. This field of cost sensitive mining is motivated by applications such as marketing, credit scoring and medical diagnosis, where the costs of misclassification, costs of acquiring data, budgets available and timeliness play a significant role in the quality of decision making.
A significant proportion of web content and its usage is due to the discussion-of and research-into consumer products. This workshop reviews the solutions to the ICDM-2012/CPROD1 contest to accurately identify and disambiguate consumer product mentions within a large product catalog.
The complexity of numerous social, biological, and communication systems is driving many researchers towards the adoption of data mining approaches for the analysis and control of complex networks. The workshop focus will encompass data mining algorithms and applications for communication networks, such as peer-to-peer systems, mobile ad-hoc networks, wireless sensor networks, the World Wide Web, and other complex networks, such as social networks, metabolic networks, protein-protein interaction networks and citation networks.
In midst of service applications in engineering and the increasing importance of the service sector in the global economy, services are being scientifically and much attention is being focused on service science as a means to improve productivity and underlying business process. The focus of this workshop is on empirical findings, methodological papers, and theoretical and conceptual insights related to data mining in the field of various service application areas.
The workshop focuses on preserving anonymity and privacy in data mining with an emphasis on preventing intentional or unintentional discrimination in automated decision making. Data on which models are built may be biased, corrupted or systematically missing, or the process of analysing data may be biased. As a result, inappropriately built data driven models may systematically discriminate, breach anonymity and privacy. The workshop will discuss recent advances in handling those issues.
KDCloud workshop intends to bring together researchers, developers, and practitioners from academia, government, and industry to discuss new and emerging trends in cloud computing technologies, programming models, and software services and outline the data mining and knowledge discovery approaches that can efficiently exploit this modern computing infrastructure.
This workshop will present recent advances in optimization techniques for, especially new emerging, data mining problems, as well as the real-life applications among. One main goal of the workshop is to bring together the leading researchers who work on state-of-the-art algorithms on optimization based methods for modern data analysis, and also the practitioners who seek for novel applications.
New IT breakthroughs drive the evolution and transformation of social networks and data. How to adapt to new privacy problems is a major challenge for organizations, enterprises and individuals. This workshop is providing a venue for researchers, policy makers, legal auditors and consultants to get together and discuss the recent advances for privacy and data protection on social data.
The goal of PTDM is to help closing the gap between data mining practice and theory. To this end, we intend to explore what is the essence of exploratory data mining and how to formalize it in a useful but theoretically well-founded way. Specific topics of interest include: Data mining foundations; Unified frameworks for data mining; Iterative/interactive data mining; Relational data mining; Statistical and information theoretic assessment and comparison of data mining patterns/results; Visual representation of data mining patterns/results; Lessons learned from real-life applications.
The RIKD workshop aims at presenting the recent advances in reliable knowledge discovery from data (RKDD). This year as usual the workshop focuses on theory and applications of RKDD. We encourage submissions on reliability problems/solutions for each stage of KDD process: data selection, data pre-processing, data mining, visualization, and model evaluation.
SENTIRE is the IEEE ICDM workshop series on opinion mining. The term SENTIRE comes from the Latin feel and it is root of words such as sentiment and sensation. The main aim of SENTIRE is to explore the new frontiers of opinion mining and sentiment analysis by proposing novel techniques in fields such as AI, Semantic Web, knowledge-based systems, adaptive and transfer learning, in order to more efficiently retrieve and extract social information from the Web.
Online social networks have witnessed explosive growth in recent years. The use of web-based social features intersects with nearly every facet of our lives, defining and evolving the nature of our social interactions. This workshop will provide a forum for academic researchers, students, practitioners, and others with an interest in online social network analysis and data mining concepts to share their ideas, network, and learn new methods for tackling complex problems in these exciting fields.
SSTDM workshop seeks to bring together researchers from academia, government, and geospatial industry to facilitate cross-disciplinary exchange of ideas in the area of spatial and spatiotemporal data mining.
Entity related research such as entity extraction, recognition, entity relation modeling etc. is highly desired by recent advances in various Web applications such as Web search, online advertising, and social networks. Taking entity as the theme, this workshop is to bring together leading researchers in related areas to promote this important but underexplored research direction, establish the technical foundation, and assess the state of the art.
The workshop has been cancelled.
This workshop has been cancelled.
You can find the expired call for workshops here.
Jilles Vreeken (University of Antwerp, Belgium)
Charles Ling (University of Western Ontario, Canada)