  In this paper, we propose an algorithm of searching for both positive and
negative itemsets of interest which should be given at the first stage for
positive and negative association rules mining. Traditional association rule
mining algorithms extract positive association rules based on frequent
itemsets, for which the frequent itemsets, i.e. only positive itemsets of
interest are searched. Further, there are useful itemsets among the frequent
itemsets pruned from the traditional algorithms to reduce the search space, for
mining of negative association rules. Therefore, the traditional algorithms
have not come true to find negative itemsets needed in mining of negative
association rules. Our new algorithm to search for both positive and negative
itemsets of interest prepares preconditions for mining of all positive and
negative association rules.
