| 1. | The problem of fuzzy constraint in frequent itemset mining is studied
摘要研究频繁项集挖掘中的模糊约束问题。 |
| 2. | Paper presentes a new algorithm of mining frequent item sets with negative items
论文提出一种新的挖掘含负项目的频繁项集算法,即基于频繁模式树的算法。 |
| 3. | Aims at the inherent fault of the apriori algorithm , analyzes and realizes the fp - growth which does not generate candidate mining frequent itemset
针对apriori算法的固有缺陷，对不产生候选挖掘频繁项集方法- - fp - growth频集算法进行分析并加以实现。 |
| 4. | According to this novel algorithm , the set of frequent items can be derived from the idea of k - weight - estimate , and next , association rules can be discovery according to the matrix - weighted confidence
该算法首先根据k -权值估计思想找出频繁项集，然后根据矩阵加权置信度找出关联规则。 |
| 5. | Considering the defects of typical algorithm for mining frequent itemsets , this dissertation puts forward hy algorithm which is designed to mine association rules and based on the hash technique and the optimized transaction reduction technique
针对经典频繁项集挖掘算法的不足，提出了进行关联规则数据挖掘的基于散列技术和优化的事务压缩技术的hy算法。 |
| 6. | The paper propose a new means to mine multidimensional association rules based on multidimensional frequent items set by two steps . firstly we obtain inter - dimension association rules by combining data cube technique with apriori method efficiently
本文中对基于多维的频繁项集的算法进行了探索和算法优化，尤其是通过采用了维搜索和散列的技术方法而使得系统的挖掘性能大大提高。 |
| 7. | The algorithm is based on the frequent pattern tree , which uses for reference a compressed storage data structure i . e . frequent pattern tree of fp _ growth algorithm . it mines frequent item sets with negative items through extending frequent patterns on the tree
该算法借用fp _ growth算法中频繁模式树这种压缩存储事务的数据结构,通过频繁模式树进行模式扩展,挖掘含负项目的频繁项集。 |
| 8. | 3 . in the paper we research the apriori arithmetic of association rules , probe into several efficient methods to improve the apriori arithmetic , and introduce emphatically a mining method without generating candidate frequent itemsets : fp - tree
3研究关联规则apriori算法，分析了传统的关联规则理论基础、经典算法，探讨了提高apriori算法效率的几种方法，着重介绍一种不产生候选挖掘频繁项集的方法。 |
| 9. | In the paper , the means is researched to mine multidimensional association rules and a effective means based on multidimensional frequent items set by practice in students information system is found
本文通过在学生信息管理系统中的具体实践和运用，对多维关联规则数据挖掘技术进行了探索，实现了基于多维频繁项集进行多维关联规则数据挖掘的一种实用高效的方法，并建立了一个高效的学生信息关联规则挖掘系统。 |
| 10. | 4 ) we introduce a classical algorithm which can extract implication rules based on concept lattice . the algorithm builds lattice incrementally and updates the set of rules simultaneously . we modify the structure of lattic to meet our requirement of finding frequent itemsets
( 4 )介绍一种经典的基于概念格的提取蕴涵规则的算法，该算法增量式建格，同时更新规则集，我们根据需要对格结构进行相应修改，从而可以增量式获取频繁项集。 |
