Computational Aspects of Data Aggregation and Complex Data Fusion
16th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems – IPMU 2016
June 20-24, 2016, Eindhoven, The Netherlands
The IPMU conference is organized every two years with the focus of bringing together scientists working on methods for the management of uncertainty and aggregation for the exchange of ideas between theoreticians and practitioners in these and related areas.
The proceedings of IPMU-2016 will be published in Communications in Computer and Information Science (CCIS) with Springer. Papers must be prepared in the LNCS/CCIS one-column page format. For more details please refer to the Instructions for the authors.
We would like to invite the researchers to submit their contributions to the special session entitled Computational Aspects of Data Aggregation and Complex Data Fusion.
Update#1 (2016-02-03). Paper submission is now closed.
Update#2 (2016-03-15). The special session will be included in the Final Program of IPMU 2016.
Classically, the theory of aggregation focuses on mathematical aspects of data aggregation. This includes the construction and analysis of fusion functions that act on elements in the real line (means, t-norms, t-conorms, fuzzy implications), on chains, as well as other lattices.
This session is focused on data fusion tools for aggregating more complex objects – mostly their computational aspects, as in such a framework algorithms of interest are much more challenging. Special focus is on combining information from heterogeneous sources, big data aggregation, and computationally demanding complex data types.
Systems Research Institute, Polish Academy of Sciences
KERMIT, Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University
School of Information Technology