Formal Concept Analysis via Atomic Priming
2013 (English)In: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 7880, 92-108 p.Article in journal (Refereed) Published
Formal Concept Analysis (FCA) looks to decompose a matrix of objects-attributes into a set of sparse matrices capturing the underlying structure of a formal context. We propose a Rank Reduction (RR) method to prime approximate FCAs, namely RRFCA. While many existing FCA algorithms are complete, lectic ordering of the lattice may not minimize search/decomposition time. Initially, RRFCA decompositions are not unique or complete; however, a set of good closures with high support is learned quickly, and then, made complete. RRFCA has its novelty in that we propose a new multiplicative two-stage method. First, we describe the theoretical foundations underpinning our RR approach. Second, we provide a representative exemplar, showing how RRFCA can be implemented. Further experiments demonstrate that RRFCA methods are efficient, scalable and yield time-savings. We demonstrate the resulting methods lend themselves to parallelization.
Place, publisher, year, edition, pages
Dresden: Springer Berlin/Heidelberg, 2013, 7880. Vol. 7880, 92-108 p.
Formal Concept Analysis; Rank Reduction; Factorization
Research subject Applied and Computational Mathematics
IdentifiersURN: urn:nbn:se:kth:diva-174032DOI: 10.1007/978-3-642-38317-5_6ScopusID: 2-s2.0-84883404234OAI: oai:DiVA.org:kth-174032DiVA: diva2:856941
11th International Conference on Formal Concept Analysis, ICFCA 2013; Dresden; Germany; 21 May 2013 through 24 May 2013
QC 201509282015-09-262015-09-262015-09-28Bibliographically approved