基于抗体选择策略的克隆挖掘算法

针对如何有效地利用大量的原始数据分析现状来预测未来的问题,基于抗体选择策略提出一种克隆选择挖掘算法。通过评估抗体的支持度、可信度和亲和度,求得有效的关联规则。实验结果表明,该算法能较快地获得可理解的规则,并且具有较高的准确率。     

P2P存储系统副本一致性维护策略

副本策略是提高P2P存储系统的可扩展性、容错性、可用性的有效手段。随着新的应用发展,P2P中副本应用从只读静态文件共享转变为读写动态文件交互,副本的一致性维护变得越来越重要。提出一种副本信息传播树的维护策略,该策略把文件副本的相关信息保存在二叉树上,通过订阅和取消订阅算法维护副本的一致。实验证明该策略能有效减少维护开销,避免相关问题的出现。     

Tree pattern mining with tree automata constraints

Most work on pattern mining focuses on simple data structures such as itemsets and sequences of itemsets. However, a lot of recent applications dealing with complex data like chemical compounds, protein structures, XML and Web log databases and social networks, require much more sophisticated data structures such as trees and graphs. In these contexts, interesting patterns involve not only frequent object values (labels) appearing in the graphs (or trees) but also frequent specific topologies found in these structures. Recently, several techniques for tree and graph mining have been proposed in the literature. In this paper, we focus on constraint-based tree pattern mining. We propose to use tree automata as a mechanism to specify user constraints over tree patterns. We present the algorithm CoBMiner which allows user constraints specified by a tree automata to be incorporated in the mining process. An extensive set of experiments executed over synthetic and real data (XML documents and Web usage logs) allows us to conclude that incorporating constraints during the mining process is far more effective than filtering the interesting patterns after the mining process.     

基于结构标记树的XML可查询压缩方法

针对支持查询的XML数据压缩方法存在的路径和数据重复等问题,通过去除XML数据中的重复路径,简化XML数据结构,提出结构标记树的概念及其生成算法,设计一种基于结构标记树的可查询XML数据压缩方法SSTQC,对XML数据进行压缩和组织查询。SSTQC一次扫描XML文档,具有较好的的压缩性能和查询效率。     

二层以太网中最优组播树的构建方法

针对二层以太网难以构建最优组播树且收敛速度慢的问题,提出一种新的最优组播树构建方法。该方法将IS-IS协议用于二层以太网络最短路径树的计算,通过扩展链路状态包的CLV改进其通告机制,以便构建最优组播树,且网络拓扑发生变化时可快速重构此最优组播树。测试结果表明,该方法可将组播树的收敛时间从现有方法的10 s~20 s缩短到50 ms,并能确保该组播树为最优组播树。     

基于约束的可能性XML条件计算

将约束引入到可能性XML时,因分布节点值的不确定性,XML文档无法检验对涉及分布节点的约束的合法性。在一些场景中,要返回给用户符合约束的查询结果和概率,通常没有考虑去除不可能域分布来做条件计算,得出的并不是准确概率。为此,提出一种可能性XML的概念,给出可能性XML中可能域和约束的有效表达,通过提出的方案解决条件计算和准确概率计算的问题。实验结果表明,该算法的效率较高,条件计算后的结果更能被用户接受。     

动态故障树割序集分析的模块化方法

针对割序集模型较高的复杂度,提出静态子树模块化和动态子树模块化2种简化方法。利用模块化方法将动态故障树划分为多个静态子树和动态子树。对完全由静态门构成的静态子树采用二叉决策图计算其发生概率;对动态子树采用割序集模型进行分析,将其中包含的静态子树作为一个整体进行处理。通过实例阐述模块化方法的应用过程,算例分析结果表明,该方法能有效降低割序集模型的复杂度。     

具有多维特征的WSN路由协议研究

为实现不同地理维数数据类型的合理融合,提出一种基于通用搜索树(GiST)的分簇拓扑结构。利用叶节点的位置信息建立簇,通过GiST体系结构算法对区域内的所有簇进行分块组织,建立树形拓扑结构。仿真结果表明,GiST体系结构算法具有良好的多维特性,可快速进行不同维数结构间的融合。建立的结构与其他拓扑结构相比,网络传输效率较高,网络生命周期较长。     

基于树核函数的英文句子情感分类研究

最近几年,由于在线客户评论信息飞快地增长。如何把这些信息分类为正向和负向情感是一个迫切需要解决的问题。提出了一种细粒度级别(句子级别)的情感分类方法,该方法在SVM分类器中使用了树核和复合核函数来进行句子级别情感的分类。实验结果表明在句子级别的情感分类中树核和复合核的方法比线性核具有更佳的性能。     

A bounded distance metric for comparing tree structure

Comparing tree-structured data for structural similarity is a recurring theme and one on which much effort has been spent. Most approaches so far are grounded, implicitly or explicitly, in algorithmic information theory, being approximations to an information distance derived from Kolmogorov complexity. In this paper we propose a novel complexity metric, also grounded in information theory, but calculated via Shannon's entropy equations. This is used to formulate a directly and efficiently computable metric for the structural difference between unordered trees. The paper explains the derivation of the metric in terms of information theory, and proves the essential property that it is a distance metric. The property of boundedness means that the metric can be used in contexts such as clustering, where second-order comparisons are required. The distance metric property means that the metric can be used in the context of similarity search and metric spaces in general, allowing trees to be indexed and stored within this domain. We are not aware of any other tree similarity metric with these properties.