| 1. | Efficient mining algorithm for frequent pattern in intrusion detection
基于最小完美哈希函数的数据挖掘算法 |
| 2. | We develop an simple encoding algorithm so that frequent patterns can be easily analyzed , and compared
我们设计了一个简单的编码算法以便容易地分析和比较频繁模式。 |
| 3. | All urge people to put more and more attentions to the frequent pattern mining in graphs
同时，随着各种新应用的不断推出，人们将注意力逐步向图中的频繁模式的产生问题转移。 |
| 4. | Frequent pattern mining technology in data mining is for mining characteristic patterns with frequent occurrences among data
数据挖掘中的频繁模式挖掘技术专注于发现数据中频繁出现的特征模式。 |
| 5. | The algorithm eliminates the redundancy brought by isomorphic overlapped sub trees , and assures the minimum of frequent pattern
本算法剔除了同构交叠子树带来的冗余,保持了模式在一棵树上的最小性。 |
| 6. | 2 . research of mining relationship patterns in multiple time series an algorithm for discovery frequent patterns in multiple time series will be proposed
2 )多时间序列间关联模式挖掘研究针对更有分析价值的多序列关联模式，进一步提出一种新颖的关联模式挖掘方法。 |
| 7. | Next , after near 10 years research and development , the most essential phase in association rules mining , frequent pattern acquirement , and its techniques have been improved dramatically
其次，在经历了近10年的发展以后，关联规则挖掘中至关重要的频繁模式获取技术得到了很大的发展。 |
| 8. | It is based on the fact that unique labeled graph can be transformed into the format of itemset , on which recent 10 years research on frequent pattern mining can be applied
由于唯一标号图能转换为项集的形式，这就能充分利用近10年来的研究成果。唯一不同的地方是在连通性上的进一步考虑。 |
| 9. | After that , we designed a new data model , called inter - related successive trees irst , to find frequent patterns from multiple time series without generation lots of candidate patterns
在挖掘算法实现上，根据序列特征模式的有序性和重复性，提出了一种无须生成大量的候选模式集的互关联后继树挖掘算法。 |
| 10. | The work in the dissertation is strictly bounded in such field by following the two phases , frequent pattern acquirement and rules generation , to deep into the extended research step by step
本文的工作在关联规则挖掘的范畴以内，根据关联规则的生成的二个主要阶段：频繁模式的获取和关联规则的生成进行了深入的拓展性研究。 |
