We are in the era of big data. Massive datasets surpassing terabytes and petabytes from all different real world applications, from social network analysis to bioinformatics, are now commonplace. They arise in numerous settings in science, government, and enterprises. Because of the rapid development of the hardware technology such as storage and communication systems, there are more and more digitized data that are readily available. Effective utilization and making sense of those data has been one research topic that has attracted huge amounts of interests from different fields, where Data Mining, as a field of mining knowledge and insights from massive data, plays an important role. One important aspect for exploring big data is interdisciplinarity, i.e., the data scientists need to work with domain experts owning those data to understand their needs and explain them the mined data-driven insights, get their inputs and feedbacks, and update the model to make it more accurate. This process will be iterated over time. Because a lot of interactions are involved between domain experts and computational models in this whole process, we usually call it interactive mining.
There are several important and challenging aspects of the interactive mining process:
The focus of this workshop is to gather together the researchers from all relevant fields to share their experience and opinions on interactive mining of big data, with emphasis on interactivity and effective integration of techniques from data mining, visualization and human-computer interaction. In other words, we intend to explore how the best of these different but related domains can be combined such that the sum is greater than the parts. We will solicit a list of program committee members who are very active in this area, and guarantee each submission gets peer reviewed by at least three of them. We will also invite three to four high-profile researchers as keynote speakers and deliver invited talks.
Topics of interests for this workshop include, but are not limited to:
Interactive mining algorithms, Visualization techniques for interactive mining, Demo systems for interactive mining, Never-ending learning, Online learning, Active learning technologies Stream mining, Collective intelligence, Stochastic methods, Computer-human interaction and user study, System and architecture for supporting interactive mining, Complexity and theoretical analysis, Domain adaptation methods, Privacy-preserving issues in interactive mining, Open challenge discussions