New applications of data mining, such as in biology, bioinformatics, or sociology, are faced with large datasets structured as graphs. We present an efficient algorithm for minin...
Recent research in data mining has progressed from mining frequent itemsets to more general and structured patterns like trees and graphs. In this paper, we address the problem of...
To increase the relevancy of local patterns discovered from noisy relations, it makes sense to formalize error-tolerance. Our starting point is to address the limitations of state...
In this paper, we examine the performance of frequent pattern mining algorithms on a modern processor. A detailed performance study reveals that even the best frequent pattern min...
In many application domains (e.g., WWW mining, molecular biology), large string datasets are available and yet under-exploited. The inductive database framework assumes that both s...