### Citations

3471 |
UCI repository of machine learning databases
- Blake, Merz
- 1998
(Show Context)
Citation Context .... The experimental results show the partitioning algorithm is much faster than NextClosure algorithm. Real data (see table 1) for our experiment comes from machine learning benchmarks: UCI repository =-=[3]-=-. The algorithm is easy to be used to extract some interesting concepts according to the density of the concepts such as big concepts or small concepts. For example, the figure 8 illustrates the run t... |

1220 |
Formal concept analysis - mathematical foundations.
- Ganter, Wille
- 1999
(Show Context)
Citation Context ...e rules, extracting the hierarchical relation among formal concepts, etc. The core of FCA is concept lattice. Theoretical foundation of concept lattice is derived from the mathematical lattice theory =-=[2, 7]-=- that is a popular mathematical structure for modeling conceptual hierarchies. Concept lattice also provides an effective tool of knowledge visualization. Concept lattice facilitates exploring, search... |

826 |
Lattice Theory
- Birkhoff
- 1967
(Show Context)
Citation Context ...e rules, extracting the hierarchical relation among formal concepts, etc. The core of FCA is concept lattice. Theoretical foundation of concept lattice is derived from the mathematical lattice theory =-=[2, 7]-=- that is a popular mathematical structure for modeling conceptual hierarchies. Concept lattice also provides an effective tool of knowledge visualization. Concept lattice facilitates exploring, search... |

136 |
Two basic algorithms in concept analysis.
- Ganter
- 2010
(Show Context)
Citation Context ...l results We have implemented the algorithm in Java to generate concepts. We test the algorithm in some real data and simulation data. We compare the partitioning algorithm with NextClosure algorithm =-=[6]-=-. Experimental comparisons of lattice-based algorithms show that NextClosure algorithm is one of the best for large and dense data [8, 5]. The preliminary experimental results in figure 7 show the eff... |

133 | Comparing performance of algorithms for generating concept lattices.
- Kuznetsov, Obiedkov
- 2002
(Show Context)
Citation Context ... We compare the partitioning algorithm with NextClosure algorithm [6]. Experimental comparisons of lattice-based algorithms show that NextClosure algorithm is one of the best for large and dense data =-=[8, 5]-=-. The preliminary experimental results in figure 7 show the efficiency of the algorithm. In the the experimental results, the run time of partitioning algorithm is the total time of all subspaces mini... |

122 |
Data Mining.
- Adriaans, Zantinge
- 1996
(Show Context)
Citation Context ...cit, hidden in large data, and should be derived from data. We therefore should extract the knowledge from large data with the techniques such as data mining or KDD (Knowledge Discovery in Databases) =-=[16, 4, 1]-=-. The techniques of data mining are widely used in research and application to look for relationships and knowledge that are implicit in large volumes of data and are interesting in the sense of impac... |

3 |
Nguifo. How well go lattice algorithms on currently used machine learning testbeds
- Fu, Mephu
(Show Context)
Citation Context ... We compare the partitioning algorithm with NextClosure algorithm [6]. Experimental comparisons of lattice-based algorithms show that NextClosure algorithm is one of the best for large and dense data =-=[8, 5]-=-. The preliminary experimental results in figure 7 show the efficiency of the algorithm. In the the experimental results, the run time of partitioning algorithm is the total time of all subspaces mini... |

1 |
JETAI Special Issue on Concept Lattice for KDD. Taylor and Francis, 2002. ID Objects Attributes Closed itemsets soybean-small d1 47 79 3253 car d2
- Nguifo, Liquiere, et al.
(Show Context)
Citation Context ...]. The application of concept lattice has been an area of active and promising research in various fields such as knowledge discovery, information retrieval, software engineering and machine learning =-=[10, 9]-=- and bioinformatics [11, 15, 14, 18]. In this paper, we propose a framework of distributed knowledge sharing in digital ecosystem. We also propose a scalable lattice-based algorithm to discover hierar... |