| 1. | Review of the optimization and analysis of apriori algorithm
算法分析与改进综述 |
| 2. | Applying apriori algorithm to sequential patterns mining
算法进行序列模式挖掘 |
| 3. | An improved apriori algorithm for mining association rules
算法的一个改进 |
| 4. | Improvement in apriori algorithm and using in logistics information mining
算法的改进及其在物流信息挖掘中的应用 |
| 5. | Predicting prosodic parameters for speech synthesis with improved apriori algorithm
算法对语音合成中韵律参数的预测 |
| 6. | An improved algorithm of apriori
的改进算法 |
| 7. | Shown by analysis , the bottleneck of the algorithm apriori is candidate itemsets generation and test
分析得知， apriori算法的瓶颈是候选集的产生及验证。 |
| 8. | Apriori algorithms , which was advanced by rakesh agrawal , is the most classic algorithms
关联规则最经典的算法是由rakeshagrawal等人提出的apriori算法。 |
| 9. | We experimentally compare the new algorithm against apriori algorithm obtaining satisfied improvements
通过对ardbet算法和apriori算法的比较，得到了比较满意的结果。 |
| 10. | The former algorithm is based on the apriori idea and the latter uses the features in fp - growth
两个算法中，前者基于apriori思想，后者则充分利用了fp - growth的特点。 |
