On the relevance of data, association rules have positive or negative association rules.

关联规则就数据项之间的相关性来说，可以有正负关联规则之分。

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According to the value of consult, association rules were classified into positive, negative and invalid association rules. The new algorithm could find out the negative-item-contained rules.

利用参考度将关联规则分为正关联规则、负关联规则和无效关联规则，从而可以用算法挖掘带有负项的关联规则。

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Defining interestingness and putting forward new algorithm of mining association rules including negative items.

定义兴趣度，提出挖掘含负属性项关联规则算法。

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The negative items are introduced to expressions, and the traditional association rules are expanded to the general association rules with positive and negative items.

在表达式中引入负项目，将这种传统的关联规则扩展成包含正、负项目的一般化关联规则。

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Provides a practical updating algorithm for negative incremental association rules in which the size of data sets is reduced, with the supporting and confidence limits unchanged.

提出了一种实用的在支持度和置信度不变的情况下数据集规模减小的负增量关联规则更新算法。

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Absrtact: In the study of updating algorithm for incremental association rules, litde research has been done on the negative incremental updating algorithm.

摘 要：在增量式关联规则更新算法的研究中，关于负增量式更新算法的研究比较少。

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This paper provides a practical maintenance algorithm for negative incremental association rules in which the size of data sets is reduced, with the supporting and confidence limits unchanged.

提出了一种实用的在支持度和置信度不变的情况下数据集规模减小的负增量关联规则维护算法。

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In addition, when the new algorithm is mining positive association rules, it cuts out invalid rules using negative rules, and this makes the result more in line with the user's shopping behavior.

另外，新算法在挖掘正规则的同时，利用负规则裁减掉无效规则，得到的结果更符合用户的购物行为。

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In addition, when the new algorithm is mining positive association rules, it cuts out invalid rules using negative rules, and this makes the result more in line with the user's shopping behavior.

另外，新算法在挖掘正规则的同时，利用负规则裁减掉无效规则，得到的结果更符合用户的购物行为。

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