In this paper, we introduce a diamond episode of the form s1 → E → s2, where s1 and s2 are events and E is a set of events. The diamond episode s1 → E → s2 means that every...
Recent studies have proposed different methods for mining frequent episodes. In this work, we study the problem of mining closed episodes based on minimal occurrences. We study the...
An ideal outcome of pattern mining is a small set of informative patterns, containing no redundancy or noise, that identifies the key structure of the data at hand. Standard freq...
Abstract. This work aims to improve an existing time series forecasting algorithm –LBF– by the application of frequent episodes techniques as a complementary step to the model....
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...