| 1. | Study on fci mining algorithm based on concept lattice
基于概念格的频繁闭项集增量挖掘算法研究 |
| 2. | There is no closed items in the database . this command is not available
我翻译成:由于此数据库中已无关闭项，本命令无效。 |
| 3. | Frequent closed itemsets rules imply all the association rules but greatly reduce the rules number
频繁闭项集规则蕴含了所有关联规则，数目却大为减少。 |
| 4. | In order to tackle this problem , recent studies raised an effective alternative , mining frequent closed itemsets rules
为此，近年的研究提出一种有效的替代手段?挖掘频繁闭项集规则。 |
| 5. | Not only realize scanning databases only one time and decrease i / o resources consumption , but also improve storage efficiency of data structure and time efficiency of mining algorithm
不仅实现了事务数据库的一次扫描，减少了i / o代价，而且提高了数据结构的存储空间效率和频繁闭项集挖掘算法的执行时间效率。 |
| 6. | This paper discussed the clustering algorithms based on the longest frequent closed itemsets using frequent - pattern tree , concluded that in some situation it is inapproriate to using this technique to classifing data in data mining
摘要针对采用频繁模式树构造的最长频繁闭项集的聚类算法，提出该算法在一些特殊环境下可能产生的误差，因而建议在一些应用情况下，不宜采用该算法进行数据挖掘中的数据分类。 |
| 7. | A new and more advantageous lattice structure for rule extracting is proposed based on the theory of concept lattice and the concept of closed item set in this thesis . then , an incremental algorithm based on closed label for constructing lattice and algorithm for rules extracting are developed
本文基于概念格理论和闭项集的概念，提出了一种新的更有利于规则提取的格结构，给出了相应的基于闭标记的渐进式构造算法和规则提取算法。 |
| 8. | This paper presents the directed itemsets graph to store the information of frequent itemsets of transaction databases , and puts forward the trifurcate linked list storage structure of directed itemsets graph , and provides the mining algorithm of frequent closed itemsets based on directed itemsets graph
摘要利用了有向项集图来存储事务数据库中有关频繁项集的信息，提出了有向项集图的三叉链表式存储结构和在于有向项集图的频繁闭项集挖掘算法。 |
| 9. | Mining of frequent closed itemsets greatly improve the rules mining effiency and effectivity of the resulting rules , hence release the users of the burden . we implement the frequent closeu itemsets mining algorithm fcis and the frequent closed itemsets rules mining algorithm ci _ rules . experiments diplay that compared with the latest published algorithm - the closet algorithm proposed by jiawei han , our algorithm is more than two malgtitudes faster and has fabulous scalability ; ci _ rules algorithm overtakes fpmine - spf algorithm by more than two malgtitudes and has extraordinary scalablity
实验表明，在相同数据集上，与已发表的最新成果? han的closet算法相比，本文算法fcis速度提高两个数量级以上，并有极好的可伸缩性； ci _ rules算法挖掘频繁闭项集规则的运行速度较fpmine - spf算法挖掘关联规则的速度快两个数量级以上，并有非凡的可伸缩性。 |
