【作者】 李重周；

【导师】 杨君锐；

【作者基本信息】 西安科技大学 ， 计算机应用技术， 2008， 硕士

【摘要】 数据挖掘是致力于数据分析和理解、揭示数据内部蕴涵知识的技术,它是未来信息技术应用的重要方法之一。关联规则挖掘是数据挖掘中一个很重要的研究领域。关联规则挖掘算法是关联规则数据挖掘研究中的主要内容,迄今为止已提出了许多高效的关联规则挖掘算法。本文首先对数据挖掘的基本概念、数据挖掘的基本过程和数据挖掘的研究热点等方面进行了探讨,并对关联规则数据挖掘的经典算法Apriori进行了较详细的分析和研究,在此基础上,提出了一种新的不产生候选项集及少量扫描数据库来挖掘频繁项集的超集树算法SI_Tree。该算法通过搜索数据库,一次性的找出当前项的所有超集从而获得频繁项集,经实验验证,产生了较好的效果。然后,通过对盲文软件系统的研究,针对传统盲文软件系统中存在的问题,并在充分考虑关联规则挖掘算法特性的基础上,再采取不断扫描挖掘对象,组成一个Web信息元数据库,找出其中相互关联的部分,并对其进行分类等方法和手段,将超集树关联规则挖掘方法应用到盲文软件系统中,从而使盲文软件在网站访问时,达到快速访问相关内容的目的。最后,针对关联规则挖掘中可能产生许多无效规则的问题,在对兴趣度度量方法进行研究的基础上,提出了一种旨在反映项目集之间紧密性、稀有性和简洁性的新的度量方法-紧密度(性),并利用该度量方法给出了一个基于紧密性的兴趣度挖掘算法,同时将这种挖掘方法应用到盲文软件的网站访问中。经实验验证,在盲文软件的网站访问中应用基于紧密性的兴趣规则挖掘方法的访问效率要优于基于超集树的关联规则挖掘方法。更多还原

【Abstract】 Data mining is a technique that aims to analyze and understand large source data and reveal knowledge hidden in the data. It has been viewed as one of important ways in information processing. Association rule mining is a very important research field in data mining. The research on the algorithms of association rule mining is a key task in data mining of association rule. Many highly efficient algorithms in the field have been put forward for mining association rules so far.At first, the problems on the fundamental concepts of data mining, the main process of data mining, the key research of data mining and so on were inquired in the thesis. The classical algorithm Apriori in data mining of association rule was analysed and studied more thorough. Then a new Super-Items Tree(SI_Tree) algorithm without candiddte items and in mining frequent itemsets based on database scaned few was put forward. It mines frequent itemsets through all super items of the current items found only one by scaning database. The experimental results show that the algorithm has better performance.Then, the problems in the traditional Braille software system were sloved that based fully on the characteristic of association rule mining algorithm after Braille software was studied. Those were that searches all of the objects in the website constantly, makes up a Web database, finds the items which associate each other from the Web database, classes them and so on. The algorithm of super item tree for association rule mining was applied to Braille software. So that the speed to access to the web contents in Braille software was improved.Finally, a new way about the question that association rule mining can bring many unavailable association rules was presented after the interestingness in association rules mining was researched. This way was called the impaction which aimed the report of closeness、singularity and concision among the items. An algorithm of interesting mining based on the impaction was presented by the way. Also the algorithm was applied to access to the Web contents in Braille software. The experimental results show that the way has more efficient than super item tree way when the contents of Web were accessed in Braille software.更多还原