NextPriorityConcept: A new and generic algorithm computing concepts from complex and heterogeneous data

In this article, we present a new data type agnostic algorithm calculating a concept lattice from heterogeneous and complex data. Our NextPriorityConcept algorithm is first introduced and proved in the binary case as an extension of Bordat's algorithm with the notion of strategies to select onl...

Full description

Saved in:
Bibliographic Details
Published in:Theoretical computer science 2020-12, Vol.845, p.1-20
Main Authors: Demko, Christophe, Bertet, Karell, Faucher, Cyril, Viaud, Jean-François, Kuznetsov, Sergei O.
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computer Science
Formal Concept Analysis
Heterogeneous data
Information Retrieval
Lattice
Pattern structures
Strategies
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this article, we present a new data type agnostic algorithm calculating a concept lattice from heterogeneous and complex data. Our NextPriorityConcept algorithm is first introduced and proved in the binary case as an extension of Bordat's algorithm with the notion of strategies to select only some predecessors of each concept, avoiding the generation of unreasonably large lattices. The algorithm is then extended to any type of data in a generic way. It is inspired by the pattern structure theory, where data are locally described by predicates independent of their types, allowing the management of heterogeneous data.
ISSN:0304-3975
1879-2294
DOI:10.1016/j.tcs.2020.08.026