ACM International Conference on Computing Frontiers
On May 15 - 17, this years ACM International Conference on Computing Frontiers (CF ’17) was held in Siena, Italy. The conference was hosted at the University of Siena and aimed to drive scientific breakthroughs by exploring and extending emerging technologies. The conference featured three co-located workshops handling more specific topics in the area of Data Analytics, Malicious Soft- and Hardware and Embedded Systems.
As part of the Big Data Analytics Workshop (BigDAW ’17), Matthias Carnein, Dennis Assenmacher and Heike Trautmann presented their findings of the paper “An Empirical Comparison of Stream Clustering Algorithms”. Clustering is a research area in data analytics which allows to find groups of similar objects. It can be a valuable tool, e.g., to identify customer segments that share similar interests and behaviour. This allows to target each group based on their specific needs. Stream clustering extends this concept by working on a continuous stream of data which allows to apply it in real world senarios with much larger data sets. The paper explores and evaluates the most popular algorithms in the area and identifies key strengths and weaknesses. The research helps to choose a suitable algorithm for stream clustering as well as customer segmentation and also provides valuable findings to devise new algorithms.
The published paper will be shortly available through the ACM digital library.
For more information on the Computing Frontiers Conference and Big Data Analytics workshop, please go to: http://www.computingfrontiers.org/2017/