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摘要汉译英（计算机数据挖掘方面）
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为了应对实际应用中经常遇到的频繁更新的数据，一种与时机判定相结合的关联规则增量更新算法开始被人们广泛研究。丁虎在基于数据仓库的关联规则抽样算法中给出了一种基于完全频繁项集的关联规则差异度判定方法，它能够充分表达数据集更新前后关联规则的变化，减少关联规则更新的次数，因此得到比较广泛的应用，然而这种算法在计算新增数据频繁项集时不够准确，本文将提出一种DFUP算法，该算法通过引入一个动态数据库来解决上述算法的不足。 关键字：关联规则；增量更新；时机判定；关联规则差异度 |
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小小恶: 金币+20, 翻译EPI+1, ★★★★★最佳答案, 谢谢你 2015-06-19 11:03:51
小小恶: 金币+20, 翻译EPI+1, ★★★★★最佳答案, 谢谢你 2015-06-19 11:03:51
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In order to deal with the frequently updating of data in practice, association rules incremental updating algorithm combining with time judgment begun to be widely studied. DingHu gave an association rule difference degree judgment method based on the completely frequent itemsets. This method can fully express the changes of association rules before and after the dataset updating, and reduce the times of the updating of association rules, therefore, this method was widely used. However, this method is not very accurate when calculating the new frequent itemsets. DFUP algorithm is proposed in this paper, and this algorithm solves the problem of the above algorithm by introducing a dynamic database. Keywords: association rule, incremental updating, time judgment, association rule difference degree |
2楼2015-06-18 20:59:52