自适应的混沌粒子群算法优化XML文档聚类策略  

XML Document Clustering Strategy Based on Adaptive Particle Swam Optimization Algorithm with Chaos

作　　者：刘波[1,2] 杨路明[2] 邓云龙[3] 

机构地区：[1]湖南农业大学信息科学技术学院,长沙410128 [2]中南大学信息科学与工程学院,长沙410083 [3]中南大学湘雅附三医院,长沙410013

出　　处：《系统仿真学报》2009年第3期716-720,共5页Journal of System Simulation

基　　金：湖南省教育厅科研基金(05c671);湖南信息职业学院科技创新项目(108652006011)

摘　　要：为了提高海量XML文档集的聚类质量,提出了一种基于粒子群的XML自适应混沌聚类算法(简称ACPSO);为了简化XML文档相似性判定,该算法以XML键为基础,结合混沌原理与粒子群算法划分XML文档;为了加速算法的收敛性,通过对算法相关参数的自适应学习与权重调整,增强XML文档的全局寻优能力,改善XML文档聚类的质量。对比其它聚类算法,仿真表明本算法不仅能有效避免聚类停滞现象的发生,而且是一种高效的XML文档聚类方法。To improve the clustering quality of massive XML document sets, an adaptive clustering algorithm with chaos of XML document sets was proposed based on PSO （ACPSO）. To predigest similarity judgment of XML document, the algorithm is based on xml keys, chaos principles and PSO to carve up XML documents by similarity distance. While enhancing the algorithm＇s astringency, with some parameters of organize-self clustering learning and power gene optimization, the algorithm swells the capability to seek the optimization in the full XML document, and improves the clustering quality of XML documents. Contrasted with other clustering algorithms, a series of emulation experiments show that the algorithm not only avoids bringing the stagnancy in clustering but also is an effective clustering method.

关 键 词：XML文档集 XML键 混沌优化算法 自适应策略 粒子群优化算法 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]