Formal Concept Analysis
11th International Conference, ICFCA 2013, Dresden, Germany, May 21-24, 2013. Proceedings
Cellier, Peggy.
editor.
Distel, Felix.
editor.
Ganter, Bernhard.
editor.
SpringerLink (Online service)
text
gw
2013
monographic
eng
access
X, 267 p. 57 illus. online resource.
This book constitutes the refereed proceedings of the 11th International Conference on Formal Concept Analysis, ICFCA 2013, held in Dresden, Germany, in May 2013. The 15 regular papers presented in this volume were carefully reviewed and selected from 46 submissions. The papers present current research from a thriving theoretical community and a rapidly expanding range of applications in information and knowledge processing including data visualization and analysis (mining), knowledge management, as well as Web semantics, and software engineering. In addition the book contains a reprint of the first publication in english describing the seminal stem-base construction by Guigues and Duquenne; and a position paper pointing out potential future applications of FCA.
Contextual Implications between Attributes and Some Representation Properties for Finite Lattices -- Mathematical Morphology Operators over Concept Lattices -- Dismantlable Lattices in the Mirror -- Towards an Error-Tolerant Construction of EL⊥-Ontologies from Data Using Formal Concept Analysis -- Using Pattern Structures for Analyzing Ontology-Based Annotations of Biomedical Data -- Formal Concept Analysis via Atomic Priming -- Applications of Ordinal Factor Analysis -- Tri-ordinal Factor Analysis -- Formal F-contexts and Their Induced Implication Rule Systems -- User-Friendly Fuzzy FCA -- Proper Mergings of Stars and Chains Are Counted by Sums of Antidiagonals in Certain Convolution Arrays -- Modeling Ceteris Paribus Preferences in Formal Concept Analysis -- Concept-Forming Operators on Multilattices -- Using FCA to Analyse How Students Learn to Program -- Soundness and Completeness of Relational Concept Analysis -- Contextual Uniformities -- Fitting Pattern Structures to Knowledge Discovery in Big Data.
edited by Peggy Cellier, Felix Distel, Bernhard Ganter.
Computer science
Software engineering
Mathematical logic
Data mining
Artificial intelligence
Algebra
Ordered algebraic structures
Computer Science
Artificial Intelligence (incl. Robotics)
Data Mining and Knowledge Discovery
Mathematical Logic and Formal Languages
Software Engineering
Order, Lattices, Ordered Algebraic Structures
Q334-342
TJ210.2-211.495
006.3
Springer eBooks
Lecture Notes in Computer Science, 7880
9783642383175
http://dx.doi.org/10.1007/978-3-642-38317-5
http://dx.doi.org/10.1007/978-3-642-38317-5
130515
20160413122510.0
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