Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
Existing studies for mining frequent XML query patterns mainly introduce a straightforward candidate generate-and-test strategy and compute frequencies of candidate query patterns...
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, conceptual frequency rate, a new frequency definition suitable for query stream mining, is introduced. An online single-pass algorithm called OFSD (Online Frequent...