基于启发式规则优化的网页元素提取方法

网页信息提取方法中的启发式规则,是识别网页标签信息、利用网页节点分析结果、针对网页不同内容、完成信息提取的重要手段。本研究在对现有启发式规则进行研究分析的基础上,提出了几种优化的启发式规则,实现对网页标题、发布时间、来源以及正文内容等元素信息的精准提取。本研究进一步提出了运用编辑距离算法实现正文内容提取准确率的判定,并提出阙值优化方法,克服了正文提取中噪声节点多、内容识别不完全的缺陷,大大提高了提取的准确度。     

基于DWT的水印嵌入规则性能研究

在数字水印研究中,一个重要的问题是水印的不可见性与鲁棒性之间的折中。根据实际应用,数字水印的嵌入规则主要有乘性规则、加性规则和一种区域融合嵌入规则。本文主要从数字水印的抗攻击性方面,结合不同的嵌入规则,对各种常见图像攻击进行测试,在检测不同嵌入规则性能优劣的同时,为水印方法的选择与应用,提供指导和参考,以达到最佳的使用目的。     

基于维间扩展和事务压缩的关联规则算法改进

Apriori是关联规则挖掘的经典算法,在利用该算法进行医疗数据挖掘的过程中,发现其频繁项集产生过程有一些不必要的开销,为此提出了改进算法Mypriori,利用维间扩展和事务压缩策略来提高频集发现的效率,并通过实验验证了算法的有效性.     

制定规则实现邮件管理自动化

邮件管理自动化的实现,在提高邮件传递质量的同时,还能避免不必要的垃圾邮件。     

基于聚类分析的新书推荐

针对大多数图书馆管理系统中的个性化服务中的新书推荐只是定时将新到馆的图书罗列出来让读者浏览进行推荐,推荐效果差的问题。本文在比较三大常用的推荐技术的优缺点后,采用基于聚类分析的推荐算法推荐新书,并具体给出实现的方法。     

引入关联分析的用户行为信任评估在云计算平台中的研究

关联规则是数据挖掘的重要方法。随着国内外云计算应用及研究的不断推进,云计算的安全性成为云计算的核心问题之一。通过进行用户的状态行为关联分析,提取信任信息,结合可信云的思想,提出一个云计算下基于信任的防御系统模型。     

Modal logic as metalogic

The goal of this paper is to show how modal logic may be conceived as recording the derived rules of a logical system in the system itself. This conception of modal logic was propounded by Dana Scott in the early seventies. Here, similar ideas are pursued in a context less classical than Scott's.First a family of propositional logical systems is considered, which is obtained by gradually adding structural rules to a variant of the nonassociative Lambek calculus. In this family one finds systems that correspond to the associative Lambek calculus, linear logic, relevant logics, BCK logic and intuitionistic logic. Above these basic systems, sequent systems parallel to the basic systems are constructed, which formalize various notions of derived rules for the basic systems. The deduction theorem is provable for the basic systems if, and only if, they are at least as strong as systems corresponding to linear logic, or BCK logic, depending on the language, and their deductive metalogic is not stronger than they are.However, though we do not always have the deduction theorem, we may always obtain a modal analogue of the deduction theorem for conservative modal extensions of the basic systems. Modal postulates which are necessary and sufficient for that are postulates of S4 plus modal postulates which mimic structural rules. For example, the modal postulates which Girard has recently considered in linear logic are necessary and sufficient for the modal analogue of the deduction theorem.All this may lead towards results about functional completeness in categories. When functional completeness, which is analogous to the deduction theorem, fails, we may perhaps envisage a modal analogue of functional completeness in a modal category, of which our original category is a full subcategory.     

Supporting inconsistent rules in database systems

When a set of rules generates (conflicting) values for a virtual attribute of some tuple, the system must resolve the inconsistency and decide on a unique value that is assigned to that attribute. In most current systems, the conflict is resolved based on criteria that choose one of the rules in the conflicting set and use the value that it generated. There are several applications, however, where inconsistencies of the above form arise, whose semantics demand a different form of resolution. We propose a general framework for the study of the conflict resolution problem, and suggest a variety of resolution criteria, which collectively subsume all previously known solutions. With several new criteria being introduced, the semantics of several applications are captured more accurately than in the past. We discuss how conflict resolution criteria can be specified at the schema or the rule-module level. Finally, we suggest some implementation techniques based on rule indexing, which allow conflicts to be resolved efficiently at compile time, so that at run time only a single rule is processed.An earlier version of this work appeared under the title Conflict Resolution of Rules Assigning Values to Virtual Attributes inProceedings of the 1989 ACM-Sigmod Conference, Portland, OR, June 1989, pp. 205–214.Partially supported by the National Science Foundation under Grant IRI-9157368 (PYI Award) and by grants from DEC, HP, and AT&T.Partially supported by the National Science Foundation under Grant IRI-9057573 (PYI Award), IBM, DEC, and the University of Maryland Institute for Advanced Computer Studies (UMIACS).     

一种高效挖掘冠心病医案关联规则的仿真研究

研究中医冠心病医案,高效挖掘有益信息规则问题,由于中医医案数据量大、关联性强,针对传统的关联规则挖掘算法处理中医医案数据时存在效率低、收敛速度慢及漏报规则等问题,提出一种小生境技术和基因表达式编程相结合的挖掘关联规则的方法。通过惩罚函数设置支持度阈值,利用小生境技术执行小生境演化、融合算法,结合基因表达式编程算法操作简单、鲁棒性强的优势搜索强关联规则,有效避免了算法早熟,解决了规则冗余。针对治疗冠心病的中医医案进行了验证性实验,实验结果表明,改进算法在提取有效信息的效率上有较大的提高,挖掘结果对冠心病中医临床诊治具有一定的参考价值。     

基于改进蚁群算法的模糊控制器优化设计

研究控制器优化问题,由于模糊控制系统参数无法同时优化,使得系统选择参数困难,使系统控制效果存在一定的缺陷,安全性和可靠性降低。为解决上述问题,提出了一种多种群进化蚁群算法对模糊控制器优化设计。采用懒蚂蚁效应的改进蚁群算法进行优化,在传统蚁群算法的基础上,采用多个种群并行,对算法的初始化、路径构建以及信息素更新改进,并引入到模糊控制器的隶属函数、模糊规则的优化搜索中,搜索出适应于不同控制阶段的模糊控制器参数及控制规则,并进行仿真。仿真结果证明了改进算法对模糊控制器的参数具有良好的搜索速度和精度,使系统有很强的鲁棒性。