| 1. | Statistical analysis of the correlation between proline cis peptide bonds and amino acid sequences
脯氨酸顺式肽键与氨基酸序列关联的统计分析 |
| 2. | At last , this paper proposed new methods of recommending web pages to indicate the purpose of web site ' s managers
本文针对电子商务网站的具体环境，提出了新的基于序列关联规则的个性化推荐方案和基于支持度排序树的个性化推荐方案。 |
| 3. | 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。 |
| 4. | An optimized algorithm for mining association rules in hydrological time series is proposed on the foundation of the analysis of variance ( anova ) , contingency table test and the new definition of interestingness
摘要基于方差分析、列联表检验以及兴趣度的定义，提出一种挖掘水文时间序列关联规则优化算法。 |
| 5. | After giving a new gray relational degree and discussing its nature , we apply it into the correlation analysis of time series and draw a conclusion that the gray trend relational degree analysis is a successful method on correlation analysis of time series
给出了一种新的灰色关联度,讨论了其性质,并将它引入到时间序列的关联分析中.得到了时间序列关联分析的灰色方法 |
| 6. | The results of field data analysis indicate that the correlative dimension of time series of nature field is related to earth medium characteristics intently and qualitative reflect the characteristics of the distribution of electricity and construction of medium
实例分析表明，大地电磁场时间序列关联维数与地下介质特征密切相关，能定性地反映介质的电性分布与结构特征。 |
| 7. | Focusing on the e - business aspect of web mining , this paper adopted association rule mining technology and proposed a complete resolve method . this paper proposed new opinions and methods about the process of data preparing 、 mine algorithm and personalized recommendation
本文针对web挖掘中的电子商务环境，采用序列关联规则挖掘的方法，提出了一套完整的个性化推荐解决方案，对其中的数据准备、挖掘算法、个性化推荐等阶段都提出了新的见解和方法。 |
| 8. | These researches will help us to discover changing or developing principle of things , support to decision - making , etc . the thesis addresses several key technical problems of pattern mining and its search based similarity in time series , which covers feature patterns and relationship patterns mining , pattern search based similarity in time series and stream time series and issues concerning application system implementation oriented to analysis . major contributions of this thesis include : 1 . research of mining feature patterns in time series a novel method is proposed to discovery frequent pattern from time series
本文在分析时间序列特点和实际应用需求的基础上，针对时间序列的挖掘与相似性查找一些关键技术进行了研究，具体包括特征模式挖掘、多序列关联模式挖掘、相似性模式查找等方面，所做的工作和取得的创新成果体现在以下三个方面： 1 )时间序列特征模式挖掘研究首次提出了一种基于互关联后继树模型的时序特征模式挖掘方法。 |
| 9. | These researches will help us to discover changing or developing principle of things , support to decision - making , etc . the thesis addresses several key technical problems of pattern mining and its search based similarity in time series , which covers feature patterns and relationship patterns mining , pattern search based on similarity in time series and stream time series and issues concerning application system implementation oriented to analysis . major contributions of this thesis include : 1 . research of mining feature patterns in time series a novel method is proposed to discovery frequent pattern from time series
本文在分析时间序列特点和实际应用需求的基础上，针对时间序列的挖掘与相似性查找一些关键技术进行了研究，具体包括特征模式挖掘、多序列关联模式挖掘、相似性模式查找，在线相似性查找以及最终的分析应用系统开发等方面，所做的工作和取得的创新成果体现在以下五个方面： 1 )时间序列特征模式挖掘研究首次提出了一种基于互关联后继树模型的时序特征模式挖掘方法。 |
