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...
The mining of frequent sequential patterns has been a hot and well studied area—under the broad umbrella of research known as KDD (Knowledge Discovery and Data Mining)— for we...
Abstract. Due to the dynamic nature of online information, XML documents typically evolve over time. The change of the data values or structures of an XML document may exhibit some...
Ling Chen 0002, Sourav S. Bhowmick, Liang-Tien Chi...
In this paper we extend the state-of-art of the constraints that can be pushed in a frequent pattern computation. We introduce a new class of tough constraints, namely Loose Anti-m...
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...