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排序方式: 共有2413条查询结果,搜索用时 31 毫秒
61.
Jianyong Wang Yuzhou Zhang Lizhu Zhou George Karypis Charu C. Aggarwal 《Data mining and knowledge discovery》2009,18(1):1-29
In recent years we have witnessed several applications of frequent sequence mining, such as feature selection for protein
sequence classification and mining block correlations in storage systems. In typical applications such as clustering, it is
not the complete set but only a subset of discriminating frequent subsequences which is of interest. One approach to discovering
the subset of useful frequent subsequences is to apply any existing frequent sequence mining algorithm to find the complete
set of frequent subsequences. Then, a subset of interesting subsequences can be further identified. Unfortunately, it is very
time consuming to mine the complete set of frequent subsequences for large sequence databases. In this paper, we propose a
new algorithm, CONTOUR, which efficiently mines a subset of high-quality subsequences directly in order to cluster the input
sequences. We mainly focus on how to design some effective search space pruning methods to accelerate the mining process and
discuss how to construct an accurate clustering algorithm based on the result of CONTOUR. We conducted an extensive performance
study to evaluate the efficiency and scalability of CONTOUR, and the accuracy of the frequent subsequence-based clustering
algorithm. 相似文献
62.
Mao-Zu Guo Jun Wang Chun-yu Wang Yang Liu 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2009,13(12):1143-1151
TagSNP selection, which aims to select a small subset of informative single nucleotide polymorphisms (SNPs) to represent the
whole large SNP set, has played an important role in current genomic research. Not only can this cut down the cost of genotyping
by filtering a large number of redundant SNPs, but also it can accelerate the study of genome-wide disease association. In
this paper, we propose a new hybrid method called CMDStagger that combines the ideas of the clustering and the graph algorithm,
to find the minimum set of tagSNPs. The proposed algorithm uses the information of the linkage disequilibrium association
and the haplotype diversity to reduce the information loss in tagSNP selection, and has no limit of block partition. The approach
is tested on eight benchmark datasets from Hapmap and chromosome 5q31. Experimental results show that the algorithm in this
paper can reduce the selection time and obtain less tagSNPs with high prediction accuracy. It indicates that this method has
better performance than previous ones. 相似文献
63.
Isaac J. Sledge Timothy C. Havens Jacalyn M. Huband James C. Bezdek James M. Keller 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2009,13(12):1125-1142
As humans, we have innate faculties that allow us to efficiently segment groups of objects. Computers, to some degree, can
be programmed with similar categorical capabilities, which stem from exploratory data analysis. Out of the various subsets
of data reasoning, clustering provides insight into the structure and relationships of input samples situated in a number
of distributions. To determine these relationships, many clustering methods rely on one or more human inputs; the most important
being the number of distributions, c, to seek. This work investigates a technique for estimating the number of clusters from a general type of data called relational
data. Several numerical examples are presented to illustrate the effectiveness of the proposed method. 相似文献
64.
Efrat Blumenfeld-Lieberthal 《Networks and Spatial Economics》2009,9(3):427-458
This paper presents an analysis of the topology of transportation networks within different systems of cities. Urban entities
and their components are complex systems by their nature; there is no central force that affects their spatial structure.
Thus, we study transportation networks within different countries as complex networks. Based on the above, we consider cities
as nodes, while direct air and railways routes represent the links. We present characteristics of these networks including
their degree and clustering coefficient. Transportation networks can be used as an indicator of economic activity between
cities. Cities with strong economic relationship are characterized by high volume of connectivity. Our findings suggest that
the topology of the analyzed transportation networks can be used to classify the countries they belong to based on their economic
development.
相似文献
Efrat Blumenfeld-LieberthalEmail: |
65.
在分析了现有分布式数据挖掘算法的运行机制和P2P技术具有无中心、不同步等特点的基础上,通过扩展经典K-mean算法的迭代过程,设计了一种能够用于P2P网络的分布式数据挖掘算法。该算法只需要在直接相连的节点间传递数据,并且能使每个节点上的数据按照全局聚类的结果聚合。最后用模拟实验验证了该算法的有效性。 相似文献
66.
本文分析了聚类的思想,将免疫原理引入到遗传算法并应用于聚类分析过程中,提出了改进的免疫遗传算法(MIGA)。该算法借鉴了免疫算法中有关浓度的定义,并使用了GA算法中交叉和变异的思想。通过实验显示该方;醛法优于基本的遗传算法。 相似文献
67.
68.
基于适应度的簇划分算法研究 总被引:2,自引:0,他引:2
延长网络生存期、减少网络能量消耗是传感器网络一项重要性能指标,分簇方案是实现该目标的主要方法之一.通过分析影响簇状网能耗的主要能耗参数,引入节点适应度模型,并该模型运用到簇划分算法中,优化网络能量效率.算法是分布式簇划分算法,在簇划分过程中,通过比较节点局部区域能量比、通信代价比、节点度数综合能耗因素,决定簇首节点和成簇规模.仿真结果表明该算法能够降低簇间的通信重叠,均衡网络负载,与几种算法比较适应度分簇算法使网络生存时间增加的幅度虽然不是很大,但是使网络系统的稳定时间比其他2种能量有效的算法延长了近20%左右. 相似文献
69.
无线传感器网络中最大化簇寿命的优化模型 总被引:5,自引:4,他引:1
分簇是无线传感器网络中节省节点能量的一种有效方法.研究在传感器节点均具有数据融合能力时,网络的分簇方式以及最大化簇的寿命, 提出用簇与簇头节点的能耗向量来具体刻画每个簇能量消耗的方法,建立了最大化簇寿命的整数线性规划模型,并应用该模型分析了两种基本的分簇机制下簇的寿命,提出了对就近点分簇机制下簇结构的一种调整算法.仿真实验表明,这种调整可在缩短网络时延的同时有效地延长簇的寿命. 相似文献
70.