ICFCA 2019 is happy to announce a workshop on Formal Concept Analysis at the Big Data Era.Overview
With the advent of Big Data and the increasing number of studies towards their management and analysis, it becomes important to get a better insight into existing studies, trends and challenges and rely on promising theories such as Formal Concept Analysis together with recently developed technologies to design new, accurate and scalable solutions for big data analytics.
Big Data (BD) are very large and possibly heterogeneous and unstructured data collections defined by at least 7 V’s: Volume (e.g., zettabytes), Velocity (i.e., evolving and stream data), Variety, (e.g., text, image, video), Variability (i.e., changes in the data flow rates), Veracity (accuracy), Visualization, and Value (i.e., extracted information and knowledge).
Formal Concept Analysis (FCA) is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web, to name a few. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. The mathematical power of FCA comes from its concept lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and rule mining.
Although there are significant theoretical and practical contributions within the FCA community in a variety of topics, including the design and implementation of efficient algorithms and tools for concept lattice computation and exploitation, the goal of this workshop is to pinpoint and examine a set of important and relevant research directions in Big Data management, and see where the FCA community can very likely make significant contributions. As an example, we expect to have fruitful discussions about how Formal Concept Analysis and some of its extensions can be exploited, revisited and coupled with recent processing paradigms (e.g., MapReduce and Hadoop) to maximize the benefits of Big Data through their analysis.
The scope of BigFCA’2019 includes, but is not limited to the following topics:
All submissions of up to twelve pages must be done using the EasyChair system of the workshop (see https://easychair.org/conferences/?conf=bigfca2019) and follow the author guidelines for ICFCA’2019, i.e., the formatting instructions for the Springer LNCS style (https://www.springer.com/fr/computer-science/lncs/conference-proceedings-guidelines).
All the accepted papers will be printed in the CEUR Workshop Proceedings. Papers will be evaluated by three reviewers according to their significance, originality, technical content, style, clarity, and relevance to the workshop. At least one author of each accepted paper is expected to attend the workshop.
The authors of the best accepted papers will be asked to produce an extended release to be submitted for consideration to either a journal special issue or a Springer book.