Formal Concept Analysis for Knowledge Discovery
Formal concepts proved to be of big importance for knowledge discovery, both as a tool for concise representation of association rules and a tool for clustering and constructing taxonomies. The FCA4KD workshop aims at bringing together researchers working on diverse aspects of FCA-based knowledge extraction with the applications to fields like Computer and Information Science, Linguistics, Life and Social Sciences, Bioengineering, Chemistry, etc.
Topics of Interest
Main topics of interest include, but are not limited to:
- concept lattices and related structures
- attribute implications and data dependencies
- data preprocessing
- redundancy and dimensionality reduction
- information retrieval
- association rules and other data dependencies
Paper Submission and Publication
Papers may be submitted in PDF or Postscript format. Papers need to be formatted using the Springer Lecture Notes in Computer Science style.
The submission is to be done via EasyChair.
Change of perspective: using FCA enumeration techniques to tackle hard KDD optimization problems
Alexey Buzmakov, Sergei Kuznetsov,
Projection-chain antimonotonicity, an extension of state-of-the-art antimonotonicity class
On axiomatization of classes of domain cases based on FCA
FCA-based Approach to Machine Learning
Alexei Galatenko, Stepan Nersisyan, Vera Pankratieva
Clustering of biomedical data using the greedy clustering algorithm based on interval pattern concepts
Xenia Naidenova Vladimir Parkhomenko
An approach to modelling of self-supervised symbolic machine learning process
Aleksey Buzmakov, Evgeniya Shenkman
How did Hot and Cold Regions spend Electricity? An evidence from FCA
Dmitry Egurnov, Dmitry Ignatov
Application of Triclustering in Natural Language Processing
Danil Gizdatullin, Dmitry Ignatov, Ekaterina Mitrofanova and Anna Muratova
Classification of Demographic Sequences Based on Pattern Structures and Emerging Patterns Experimental Results Revisited
Bato Merdygeev, Sesegma Dambaeva
The converting of domain ontology into formal context
Multiple Comparisons Problem for Ordered Hypotheses Testing.