14th International Conference on Formal Concept Analysis - Supplementary Proceedings
This volume is the supplementary volume of the 14th International Conference on Formal Concept Analysis (ICFCA 2017), held from June 13th to 16th 2017, at IRISA, Rennes. The ICFCA conference series is one of the major venues for researches from the field of Formal Concept Analysis and related areas to present and discuss their recent work with colleagues from all over the world. Since it has been started in 2003 in Darmstadt, the ICFCA conference series had been held in Europe, Australia, America, and Africa.
The field of Formal Concept Analysis (FCA) originated in the 1980s in Darmstadt as a subfield of mathematical order theory, with prior developments in other research groups. Its original motivation was to consider complete lattices as lattices of concepts, drawing motivation from philosophy and mathematics alike. FCA has since then devel- oped into a wide research area with applications much beyond its original motivation, for example in logic, data mining, learning, and psychology.
The FCA community is mourning the passing of Rudolf Wille on January 22nd 2017 in Bickenbach, Germany. As one of the leading researchers throughout the history of FCA, he was responsible for inventing and shaping many of the fundamental notions of this area. Indeed, the publication of his article ”Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts” is seen by many as the starting point of Formal Concept Analysis as an independent direction of research. He was head of the FCA research group in Darmstadt from 1983 until his retirement in 2003, and remained an active researcher and contributor thereafter. In 2003, he was among the founding members of the ICFCA conference series.
For this supplementary volume, 13 papers were chosen to be published: four papers judged mature enough to be discussed at the conference and nine papers presented in the demonstration and poster session.
This paper presents recent results of studies in application of sequence-based pattern structures and emerging patterns to analysis of demographic sequences in Russia. This study is performed on data of 11 generations from 1930 till 1984 for the panel of three waves of the Russian part of Generation and Gender Survey, which took place in 2004, 2007, and 2011. The main goal is to develop methods of extracting emerging patterns (EP) with the following restrictions: the obtained patterns need to be (closed) frequent contiguous prefixes of the input sequences. These constraints were required by demographers for proper interpretation and understanding of early life course events that lead to adulthood. To fulfil this requirement we used modified FP-trees based on pattern structures of contiguous prefixes. After extraction of EP we use CAEP(Classification by Aggregating Emerging Patterns) classifier to predict gender of respondents using their demographic sequences of the first life course events. The best results in terms of TPR-FPR have been obtained for large values of minimum growth-rate parameter (with some objects left without classification).
Analysis of polyadic data (for example, multi-way tensors and n-ary relations) becomes more and more popular task nowadays. While several datamining techniques exist for (numeric) dyadic contexts, their extensions to the triadic case are not obvious, if possible at all. In this work, we study development of the ideas of Formal Concept Analysis for processing three-dimensional data, namely the so called OAC-triclustering (from Object, Attribute, Condition). Among several known methods, we have reasonably selected the most effective one and used it to propose an algorithm NOAC-triclustering for mining triclusters of similar values in real-valued triadic contexts. We have also proposed a second simple algorithm, Tri-K-Means, based on clustering algorithm K-Means, for the purpose of comparison. The experimental part demonstrates application of the algorithms to both computer-generated and real-world data.