This paper focuses on the fast update for globally frequent item sets in distributed environment when the records in database increase.
本论文主要考虑在分布式环境下数据库记录增加后，全局频繁项目集的快速更新。
The performance of this algorithm is improved noticeably by reducing the operation of producing frequent item sets and scanning large scale databases.
该算法显著减少了已有算法中产生频繁项集及扫描大规模数据库的操作，性能改善明显。
It matched user's active access sequence with frequent item sets made by association rules in real time and offered different resources to different users.
其利用关联规则得到的频繁项集实时地匹配用户的当前访问序列，对不同的用户提供不同的推荐资源。
Discovering frequent item sets is the main way of association rules mining, and it is also the focus of the study in algorithms for association rules mining.
发现频繁项集是关联规则挖掘的主要途径，也是关联规则挖掘算法研究的重点。
The results show that rules got by this method are concise and valuable. Furthermore, the generation of frequent item sets is improved remarkably, thus rapid data mining is achieved.
应用结果表明这样得到的规则简洁明确，规则具有实用价值，并且频繁集优化的效果显著，达到了快速挖掘的目的。
The results show that rules got by this method are concise and valuable. Furthermore, the generation of frequent item sets is improved remarkably, thus rapid data mining is achieved.
应用结果表明这样得到的规则简洁明确，规则具有实用价值，并且频繁集优化的效果显著，达到了快速挖掘的目的。
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