The typical Mining Association Rules algorithm is by R.
典型的关联规则发现算法是由R。
Here analyzes tow association rules, and gives the original association rules algorithm and an example shows the operational process of the algorithm.
对简单关联规则和原关联规则进行了分析比较，给出了挖掘原关联规则算法，并举例说明算法的执行过程。
This paper applies distributed data mining algorithm to IDS, takes some research on distributed pattern extraction which is based on distributed association rules algorithm.
论文把分布式数据挖掘算法运用于入侵检测系统，研究了基于分布式关联规则算法的分布式模式提取。
In this article we introduced the concepts of DW, KDD and DM, analysed the association rules algorithm and used it into mining the association rules of kinds of tax offence.
本文介绍了数据仓库、知识发现以及数据挖掘的概念，详细分析了关联规则算法，时纳税人采用的主要违法违章手段之间的关联关系进行了数据挖掘。
Based on data-distort method, we propose privacy preserving association rules mining algorithm IFB-PPARM using efficient data structure namely inverted file.
基于数据变换法，提出使用高效数据结构即倒排文件的隐私保护关联规则挖掘算法ifb - PPARM。
This paper firstly presents a power set-based association rules mining algorithm which USES pow er set as an association rules mining tool.
首次提出了利用幂集作为挖掘关联规则的工具，给出了基于幂集的关联规则挖掘算法。
Through defining information granule with binary string, we introduce an algorithm of mining association rules based on granular computing.
通过采用二进制串表示所定义的信息粒，提出了基于粒计算的关联规则挖掘算法。
The recommended algorithm of UAPOMR system includes recommendation based on transaction_clusters and recommendation based on association rules clusters.
UAPOMR系统的推荐算法包括基于事务聚类的推荐和基于关联规则聚类的推荐。
The optimal fuzzy association rules can be mined due to the optimal fixed clustering number that can be obtained by the relational competitive agglomeration algorithm.
由于关系数据的竞争聚集算法能得到优化的固定的聚类个数，因此能挖掘出优化的模糊关联规则。
According to the basic pattern of sales based on Internet and the attribute of mix marketing strategy dug out, this paper proposes a new algorithm of mining association rules based on constraints.
针对目前我国网络销售的基本模式，在已发现的组合营销策略特点的基础上，提出了一种基于约束的关联规则挖掘新算法。
Based on the mined association rules, this algorithm optimizes the storage structure of association rules, a nd extends SQL-like query statement.
在算法实现的过程中对关联规则集存储结构进行了优化，并扩展了类sQL查询语句。
An asynchronous algorithm APM has been proposed for mining association rules on Shared memory multi processor machine.
该文提出了在共享内存多处理机上采掘关联规则的异步算法apm。
This paper presents an efficient algorithm for integrating background constraints with multilevel association rules.
本文给出了一种将背景约束条件和多级关联规则相结合的高效算法。
This algorithm has been applied in association rules mining in one marketing EIS and shown that it is practical and effective.
该算法应用于某营销经理信息系统的关联规则挖掘，获得的结果表明算法是实用和有效的。
To mine temporal association rules in two events, we propose a new increment algorithm. Moreover, their experiment results are given.
同时针对双事件时态关联规则挖掘提出一个增量算法，并给出了实验结果。
Mining algorithm and prediction method of fuzzy association rules are discussed in this paper.
讨论了区间值关系数据库上模糊关联规则的挖掘算法与预测方法。
This paper presents a multi-level association rules mining algorithm DMARM which can be used in distributed environments. It can apply different thresholds at different levels.
提出了在分布式环境下对于每一层使用不同支持度的多层关联规则挖掘问题及其算法DMARM。
As for quantitative attributes, they are divided into several fuzzy sets by the competitive agglomeration algorithm, and then the algorithm for mining weighted fuzzy association rules is provided.
对数量型属性，应用竞争聚集算法将数量型属性划分成若干个模糊集，并系统地提出加权模糊关联规则的挖掘算法。
Mining association rules with ontological information bases on built domain ontology, using an algorithm of data mining, to produce semantic association rules which are more greatly satisfying users.
基于本体的关联规则挖掘，是利用构建好的领域本体，结合数据挖掘算法，产生出具有语义的更符合用户需求的关联规则。
Defining interestingness and putting forward new algorithm of mining association rules including negative items.
定义兴趣度，提出挖掘含负属性项关联规则算法。
A novel algorithm, QAR, for mining quantitative association rules and an incremental updating algorithm, IUQAR, are proposed.
提出了一种新的量化关联规则挖掘算法QAR及其增量式更新算法IUQAR。
The key idea of mining association rules for the basket data is studied and several methods to improve algorithm efficiency and rules selection are given.
对零售业销售数据关联规则挖掘算法的关键思想进行了研究，给出了各种提高算法效率的方法以及对规则选择的方法。
This paper proposes a new algorithm for mining association rules with composite items based on the FP-growth algorithm.
文章基于FP-增长算法提出了一种新的挖掘复合项关联规则的算法。
According to the value of consult, association rules were classified into positive, negative and invalid association rules. The new algorithm could find out the negative-item-contained rules.
利用参考度将关联规则分为正关联规则、负关联规则和无效关联规则，从而可以用算法挖掘带有负项的关联规则。
By modifying, the algorithm ML_DFPT can also distribute mine of cross level association rules using cross level mining information.
并通过对ML_DFPT算法进行部分修改，使算法可根据跨层挖掘信息在特定的层间挖掘出层间关联规则。
Aiming at the problem, this paper puts forward a new model of weighted association rules for solving the problem, and proposes an algorithm to discover all-weighted association rules.
针对此类问题，文章提出新的加权关联规则模型，并提出了完全加权关联规则的挖掘算法。
The stress of main memory is abated, the times of scan of database are cut down, and the algorithm executes more efficient mining of association rules in time-variant database.
该算法通过分组及时舍弃挖掘过程中生成的非频繁项目集，有效降低主存压力，减少对数据库的扫描次数，能够对时变数据库进行高效地关联规则挖掘。
The stress of main memory is abated, the times of scan of database are cut down, and the algorithm executes more efficient mining of association rules in time-variant database.
该算法通过分组及时舍弃挖掘过程中生成的非频繁项目集，有效降低主存压力，减少对数据库的扫描次数，能够对时变数据库进行高效地关联规则挖掘。
应用推荐