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## & Management

Citations: | 2 - 0 self |

### Citations

2797 |
Algorithms for clustering data
- JAIN, DUBES
- 1988
(Show Context)
Citation Context ...me appropriate and efficient technique is required so that it can cope up with the huge amount of data to be dealt in real life problems. Different algorithms have been developed over a period of time=-=[2, 3, 4, 5]-=-. These algorithms can be broadly classified into two agglomerative[6, 7, 8] and partitioning [9] methods based on the methodology used or into hierarchical or non-hierarchical solutions based on the ... |

722 | CURE: An efficient clustering algorithm for large databases
- Guha, Rastogi, et al.
- 1998
(Show Context)
Citation Context ...the huge amount of data to be dealt in real life problems. Different algorithms have been developed over a period of time[2, 3, 4, 5]. These algorithms can be broadly classified into two agglomerative=-=[6, 7, 8]-=- and partitioning [9] methods based on the methodology used or into hierarchical or non-hierarchical solutions based on the structure of solution obtained. There has always been trade off between qual... |

446 | ROCK: A robust clustering algorithm for categorical attributes’,Information System.,
- Rastogi, Shim
- 2000
(Show Context)
Citation Context ...the huge amount of data to be dealt in real life problems. Different algorithms have been developed over a period of time[2, 3, 4, 5]. These algorithms can be broadly classified into two agglomerative=-=[6, 7, 8]-=- and partitioning [9] methods based on the methodology used or into hierarchical or non-hierarchical solutions based on the structure of solution obtained. There has always been trade off between qual... |

417 | An efficient k-means clustering algorithm: Analysis and implementation.
- Kanungo, Mount, et al.
- 2002
(Show Context)
Citation Context ...me appropriate and efficient technique is required so that it can cope up with the huge amount of data to be dealt in real life problems. Different algorithms have been developed over a period of time=-=[2, 3, 4, 5]-=-. These algorithms can be broadly classified into two agglomerative[6, 7, 8] and partitioning [9] methods based on the methodology used or into hierarchical or non-hierarchical solutions based on the ... |

204 |
Chameleon: Hierarchical clustering using dynamic modeling.
- Karypis, Hail, et al.
- 1999
(Show Context)
Citation Context ...the huge amount of data to be dealt in real life problems. Different algorithms have been developed over a period of time[2, 3, 4, 5]. These algorithms can be broadly classified into two agglomerative=-=[6, 7, 8]-=- and partitioning [9] methods based on the methodology used or into hierarchical or non-hierarchical solutions based on the structure of solution obtained. There has always been trade off between qual... |

202 | Criterion functions for document clustering: experiments and analysis,
- Zhao, Karypis
- 2004
(Show Context)
Citation Context ... having documents from same class and such solution is considered as an ideal solution. Thus smaller the value of entropy better is the solution. Given a particular cluster Sr of size Nr, the entropy =-=[10]-=- of this cluster is defined to be � ��� �� � � 1 ��� � � � � � ��� � � ��� � �� � � �� where q is the total number of classes available in the dataset, and � � � is the number of documents assigned to... |

86 | Genetic algorithmbased clustering technique,”
- Maulik, Bandyopadhyay
- 2000
(Show Context)
Citation Context ...rithm. Various approaches have been adopted to enhance the speed of the algorithms by better modeling [11,12, 13]. Genetic Algorithms also have been applied to an extent for the problem of clustering =-=[1, 5, 15, 17]-=-. Most widely used partitioning algorithms use greedy approach. A widely used example of greedy approach is k-means[5] algorithm. However k-means might converge to a local optimum and its result depen... |

71 |
Computer-aided gas pipeline operation using genetic algorithms and rule learning, PHD Thesis,
- Goldberg
- 1983
(Show Context)
Citation Context ...gorithm in details with elaboration of each step. We have used concept of genetic algorithm which works iteratively and refines solution in every iteration. The steps below show the pseudo code of GA =-=[16]-=-. ISSN : 0975-3397 1875Harish Verma et. al. / (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 05, 2010, 1875-1879 t = 0; Initialize P(t); Evaluate P(t); While not (term... |

61 | Hypergraph based clustering in high-dimensional data sets: A summary of results.
- Han, Karypis, et al.
- 1998
(Show Context)
Citation Context ...be dealt in real life problems. Different algorithms have been developed over a period of time[2, 3, 4, 5]. These algorithms can be broadly classified into two agglomerative[6, 7, 8] and partitioning =-=[9]-=- methods based on the methodology used or into hierarchical or non-hierarchical solutions based on the structure of solution obtained. There has always been trade off between quality and complexity of... |

44 | Document clustering using particle swarm optimization,”
- Cui, Potok, et al.
- 2005
(Show Context)
Citation Context ...me appropriate and efficient technique is required so that it can cope up with the huge amount of data to be dealt in real life problems. Different algorithms have been developed over a period of time=-=[2, 3, 4, 5]-=-. These algorithms can be broadly classified into two agglomerative[6, 7, 8] and partitioning [9] methods based on the methodology used or into hierarchical or non-hierarchical solutions based on the ... |

19 |
A Fast Genetic K-Means Clustering Algorithm”,
- Lu, Lu, et al.
- 2000
(Show Context)
Citation Context ...rithm. Various approaches have been adopted to enhance the speed of the algorithms by better modeling [11,12, 13]. Genetic Algorithms also have been applied to an extent for the problem of clustering =-=[1, 5, 15, 17]-=-. Most widely used partitioning algorithms use greedy approach. A widely used example of greedy approach is k-means[5] algorithm. However k-means might converge to a local optimum and its result depen... |

2 |
Harmony k -means algorithm for document clustering," Data Mining and Knowledge Discovery 2009
- Mahdavi, Abolhassani
(Show Context)
Citation Context |

1 |
A novel approach toclustering using generic algorithm,” IJERIA
- Kala, Shukla, et al.
- 2010
(Show Context)
Citation Context ...rithm. Various approaches have been adopted to enhance the speed of the algorithms by better modeling [11,12, 13]. Genetic Algorithms also have been applied to an extent for the problem of clustering =-=[1, 5, 15, 17]-=-. Most widely used partitioning algorithms use greedy approach. A widely used example of greedy approach is k-means[5] algorithm. However k-means might converge to a local optimum and its result depen... |

1 | K-harmonic means - a data clustering algorithm
- Means, Data, et al.
- 1999
(Show Context)
Citation Context ...lution obtained. There has always been trade off between quality and complexity of clustering algorithm. Various approaches have been adopted to enhance the speed of the algorithms by better modeling =-=[11,12, 13]-=-. Genetic Algorithms also have been applied to an extent for the problem of clustering [1, 5, 15, 17]. Most widely used partitioning algorithms use greedy approach. A widely used example of greedy app... |

1 | Mao,“Clustering Problem Using Adaptive Genetic Algorithm,”ICNC 2005 - Chen, Han, et al. |