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:
- foundations
- concept lattices and related structures
- attribute implications and data dependencies
- data preprocessing
- redundancy and dimensionality reduction
- information retrieval
- classification
- clustering
- association rules and other data dependencies
- ontologies
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.
Participant registration
If you wish to participate in the Workshop as the guest or speaker please fill the registration form.
You can also apply for the visitor’s pass to enter HSE building there.
Preliminary Program
| 10.25-10.30 | S.O. Kuznetsov National Research University Higher School of Economics (NRU HSE) | Opening remarks |
| 10.30-11.30 | A.V. Rodin Institute of Philosophy of Russian Academy of Sciences (RAS Institute of Philosophy), NRU HSE | Truth and Justification in Knowledge Representation |
| 11.30-12.00 | N.V. Shilov Innopolis University | Designing ontology for classification and navigation in Computer Languages Universe |
| 12.00-12.30 | E.F. Goncharova National Research University Higher School of Economics (NRU HSE) | Increasing the efficiency of packet classifiers based on closed descriptions. |
| 12.30-13.15 | Lunch | |
| 13.15-13.45 | M.Yu. Bogatyrev Tula State University (TSU) | Towards constructing multidimensional formal contexts on natural language texts. |
| 13.45-14.15 | S.A. Nersisyan Lomonosov Moscow State University (MSU) | Fitting a mixture of distributions that are close to uniform on boxes |
| 14.15-14.30 | Coffee break | |
| 14.30-15.00 | D.V. Vinogradov Federal Research Center "Computer Science and Control" of Russian Academy of Sciences (FRCCSC RAS) | Random similarities computed on GPGPU |
| 15.00-15.30 | A.A. Neznanov National Research University Higher School of Economics (NRU HSE) | Ontology Based Learning and FCA-based Approach in Automatic Item Generation |