| 1. | Research on mining users ' web log sequence patterns
日志序列模式挖掘研究 |
| 2. | Recognition of user browsing sequence pattern in web log mining
日志挖掘中的用户浏览序列模式识别 |
| 3. | A data mining algorithm for sequence pattern based on grey association
一种基于灰关联的序列模式挖掘算法 |
| 4. | Research of regime transition sequence pattern : from the angle of south korea
1948年以来韩国政府的北方政策研究 |
| 5. | Application of association rules and sequence patterns algorithm to ids
关联规则和序列模式算法在入侵检测系统中的应用 |
| 6. | Sequence pattern discovery method is used to build behavioral churn model , by which we can distinguish the typical behavioral sequences of the churned customers and predict present customers " churn tendency
客户流失的行为模型采用序列模式发现方法，识别出流失客户的典型行为序列，用作流失趋势的预测。 |
| 7. | The searching space of frequent temporal sequence patterns could be reduced and the efficiency of association rule mining could be improved by projecting frequent items in time windows to prefix projected accumulation trees
将时间窗口内频繁项的信息映射到前缀映射累加树中，以降低频繁时序模式的搜索空间，提高时序关联规则的挖掘效率。 |
| 8. | To solve these problems , this thesis proposed a new model for the intrusion detection system that based on the data mining . we have discussed some key technical problems and related solutions . we apply some existing algorithms of association analysis , sequence pattern analysis , and data classification to the intrusion detection system
针对这些问题，本文采用了一种基于数据挖掘技术建立入侵检测系统的方法，讨论了该系统实现中的关键技术及解决方法，将现有的数据挖掘算法中的关联分析、序列模式分析、分类等算法应用于入侵检测系统，对入侵行为提取特征、建立规则，通过对审计数据的处理与这些特征进行匹配，检测入侵，以形成智能化的入侵检测系统。 |
| 9. | Some prediction methods were discussed , which include neural network , sequence pattern mining etc . some improvements have been applied to basic bp neural network , which can improve its convergence rate and accuracy . during the feature extaction of sequence pattern mining , we mainly take account into the hydrophobicity property and the adjacency relationship of acids , and it achieved good results
研究中把对bp神经网络的一些常用改进算法,如附加动量法、自适应学习率调整策略以及遗传算法用于bp神经网络中,这些算法的应用既避免了网络陷入局部极小,同时还提高了系统的收敛速度和预测精度。 |
| 10. | The first is the data exchange among different databases and setting up related dtd based on xml the second is taking clients analysis by using data mining technique . the third is finding the information of products use and special rules by using the sequence pattern mining in the data mining technique 。 then the article also puts forword a framework of the information system based on the services after - sale
该模型主要涉及三个方面：其一是基于xml的不同数据库之间的数据交换，建立相关的dtd ；其二是，使用数据挖掘技术进行客户分析；其三是使用数据挖掘技术中的序列模式挖掘技术获得产品使用情况和特殊规律的信息。 |
