The 3d International Workshop on Concept Discovery in Unstructured Data (CDUD 2016)
Call for papers
Concept discovery is a subdomain of Knowledge Discovery (KDD) that uses human-centered techniques such as Formal Concept Analysis (FCA), Topic Modeling, Visual Text Representations, Conceptual Graphs etc. for gaining insight into the underlying conceptual structure of the data. Traditional machine learning techniques are mainly focusing on structured data whereas most data available resides in unstructured, often textual, form. Compared to traditional data mining techniques, human-centered instruments actively engage the domain expert in the discovery process.

This workshop welcomes papers describing innovative research on data discovery techniques. Moreover, this workshop intends to provide a forum for researchers and developers of data mining instruments, working on issues associated with analyzing unstructured data. First, we are interested in methods for transforming unstructured into semi-structured information. Unstructured information such as texts or images can be tagged, keywords can be extracted from texts by means of Natural Language Processing methods, etc. For example, recently so-called Learning Representations such as Text Vectors or Visual Words have gained much attention in the domain of unstructured data. Second, in this workshop we also particularly welcome research on using human-centered instruments such as FCA to analyze unstructured and semi-structured data. Applications in which we are interested include but are not limited to Text Mining and Web Mining including forums, blogs, social sharing systems like Twitter and Facebook, mining sociological interviews, etc. We are also interested in innovative instruments for dealing with knowledge incompleteness and asymmetry.
Subject coverage:

- Applications of FCA for discovery purposes

- Association Rules and Frequent Closed Itemsets

- Biclustering and Multimodal clustering

- Conceptual Clustering

- Dealing with knowledge incompleteness and asymmetry

- Deep Learning for Text Representations

- Discovery techniques for conceptual models

- Efficient indexing and structuring algorithms

- Formal Concept Analysis

- Graph Mining

- Knowledge discovery and representation

- Natural Language Processing

- Ontology Learning from text

- Probabilistic concept discovery

- Text Kernels

- Text Mining

- Topic Modeling

- Visual Analytics
Workshop chairs

Jaume Baixeries, Universitat Politècnica de Catalunya, Catalonia

Dmitry Ignatov, National Research University Higher School of Economics, Russia

Dmitry Ilvovsky, National Research University Higher School of Economics, Russia

Alexander Panchenko, Tehcnische Universitat Darmstadt, Germany
Program committee (tentative)

Simon Andrews, Sheffield Hallam University, United Kingdom

Jaume Baixeries, Barcelona, Spain

Sergei Bartunov, National Research University Higher School of Economics

Daniel Borchmann, TU Drezden, Germany

Alexei Buzmakov, National Research University Higher School of Economics, Russia

Víctor Codocedo, LORIA, Nancy

Fritjhof Dau, SAP, Germany

Felix Distel, TU Drezden, Germany

Florent Domenach, University of Nicosia, Cyprus

Bernd Fischer, Stellenbosh University, South Africa

Boris Galitsky, Knowledge Trail, USA

Bernhard Ganter, Technical University of Dresden, Germany

Gillian Greene, Stellenbosh University, South Africa

Dmitry Ilvovsky, National Research University Higher School of Economics, Russia

Robert Jaeshke, Leibniz Universität Hannover, Germany

Yuri Katkov, EPFL, Geneva, Switzerland

Mehdi Kaytoue, LORIA, Lyon, France

Francesco Kriegel, TU Drezden, Germany

Sergei O. Kuznetsov, National Research University Higher School of Economics

Victor Lempitsky, Skolkovo Institute of Science and Technology, Russia

Natalia Loukachevitch, Lomonosov Moscow State University, Russia

Dmitry Mouromtsev, National Research University of Information Technologies, Mechanics and Optics, Russia

Xenia Naidenova, Military Medical Academy, Russia

Amedeo Napoli, LORIA, Nancy, France

Alexey Neznanov, National Research University Higher School of Economics, Russia

Artem Revenko, TU Drezden, Germany

Sergei Obiedkov, National Research University Higher School of Economics, Russia

Alexander Panchenko, Tehcnische Universitat Darmstadt, Germany

Simon Polovina, Sheffield Hallam University, United Kingdom

Uta Priss, Edinburgh Napier University, United Kingdom

Sebastian Rudolph, TU Drezden, Germany

Vladimir Selegey, ABBYY Software, Russia

Barish Sertkaya, Frankfurt University of Applied Sciences, Germany

Dominik Slezak, University of Warsaw, Poland

Rustam Tagiew, Polarez GmBH, Germany

Johanna Voelker, University of Mannheim, Germany

Rostislav Yavorskiy, National Research University Higher School of Economics, Russia
Important dates

Submission deadline: May 23, 2016

Notification of acceptance: June 08, 2016

Camera-ready due: June 23, 2016

Workshop: July 18, 2016
Proceedings

All accepted papers will be included in the workshop’s proceedings to be published online on the CEUR-Workshop web site in a volume with ISSN and indexed by Scopus. Two previous editions are available at the CEUR-Workshop web site: http://ceur-ws.org/Vol-757/ and http://ceur-ws.org/Vol-871/.
Submission Procedure

Electronic version of full paper complete with authors’ affiliations should be submitted through the conference electronic submission system.
Use the submission link http://www.easychair.org/conferences/?conf=cdud2016.
Manuscripts must be prepared with LaTeX or Microsoft Office and should follow the Springer format available at http://www.springer.de/comp/lncs/authors.html.
The maximum number of accepted papers by an individual author that can be covered by the workshop’s registration charge is 3. The papers over 12 pages are not allowed

https://cla2016.hse.ru/cdud