Abstract
In this paper we provide experimental comparison on time complexity of algorithm for creation of Generalized One-Sided Concept Lattices according to the sparseness of the input data table between standard and sparse-based implementation. It is an incremental algorithm related to FCA (Formal Concept Analysis), which is ready to be used with various attribute types and to create so-called generalized one-sided concept lattice. While these algorithms are generally exponential, in practice the complexity can be considerably reduced, e.g., for sparse input data tables. We describe sparse-based implementation of two crucial operations in our algorithm and provide experiments with different sparse data tables, where time complexity is studied for comparison of standard and sparse-based implementation of the algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
