We study the problem of mining frequent value sets from a large sensor network. We discuss how sensor stream data could be represented that facilitates efficient online mining and ...
In this paper we propose a new and elegant approach toward the generalization of frequent itemset mining to the multirelational case. We define relational itemsets that contain i...
Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
Abstract. This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory. The proposed algorithm co...
We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "brea...