The discovery of sequential patterns, which extends beyond frequent item-set finding of association rule mining, has become a challenging task due to its complexity. Essentially, ...
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...
Many real life sequence databases, such as customer shopping sequences, medical treatment sequences, etc., grow incrementally. It is undesirable to mine sequential patterns from s...
Incremental mining of sequential patterns from data streams is one of the most challenging problems in mining data streams. However, previous work of mining sequential patterns fr...
Abstract. Mobile objects have become ubiquitous in our everyday lives, ranging from cellular phones to sensors, therefore, analyzing and mining mobile data becomes an interesting p...