Abstract. Since more and more Web sites, especially sites of retailers, offer automatic recommendation services using Web usage mining, evaluation of recommender algorithms has bec...
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...
Mining massive temporal data streams for significant trends, emerging buzz, and unusually high or low activity is an important problem with several commercial applications. In th...
Mining frequent itemsets from transactional datasets is a well known problem with good algorithmic solutions. In the case of uncertain data, however, several new techniques have be...
We introduce a new algorithm for mining sequential patterns. Our algorithm is especially efficient when the sequential patterns in the database are very long. We introduce a novel...
Jay Ayres, Jason Flannick, Johannes Gehrke, Tomi Y...