大数据Apriori算法的研究与实现.docxVIP

摘 要 PAGE V 摘 要 随着信息技术的蓬勃发展和不断更新，人们利用这些技术来生产和搜集数据的能力也不断的提高，生产和有哪些信誉好的足球投注网站的数据量也越来大，到如今，这些数据可以说是海量存在的。那么，我们就需要有一种新的技术或者说是思维模式来处理分析这些海量数据，进而发现对我们有用的信息和知识，达到为提出可靠可用的决策服务的目的。由此，数据挖掘技术应时而生，应运而生，并从一诞生就以蓬勃的生命力不断发展。数据挖掘在当前成为了人工智能和数据库研究方面最值得研究的领域。数据挖掘是指从大量的数据中发现潜在的、有用的知识的过程。关联规则则是数据挖掘的主要研究内容。而发现频繁项目集则是关联规则挖掘的核心。 本文详细描述了大数据、数据挖掘、关联规则的基本内容以及数据挖掘常用的十大经典算法。在这些内容的基础上重点探讨了Apriori算法，并对经典的Apriori算法进行了分析，然后又对其做出了改进优化。 关键词：大数据，数据挖掘，关联规则，频繁项目集，Apriori算法  ABSTRACT ABSTRACT With the rapid development of information technology and constantly updated, people use these technologies to produce and collect data capacity is also increasing, production and search data is also growing, and now, these data can be said to be massive. Then we need to have a new technology or thinking model to deal with the analysis of these massive data, and then found us useful information and knowledge to achieve the purpose of making reliable decision-making services. As a result, data mining technology should be born, came into being, and from the birth of a vigorous vitality of continuous development. Data mining is currently the most worthy of study in artificial intelligence and database research. Data mining refers to the process of discovering potentially useful knowledge from a large amount of data. The association rule is the main research content of data mining. And found that frequent itemsets are the core of association rules mining. This paper describes in detail the basic content of large data, data mining, association rules and ten algorithms commonly used in data mining. Based on these contents, the Apriori algorithm is discussed, and the classical Apriori algorithm is analyzed, and then it is improved and optimized. KEY WORDS:big data,data mining,association rules,frequent itemsets,apriori algorithm  目 录 目录 TOC \o 1-3 \h \z \u 第1章　绪