Periodicals are publications which are issued at regular intervals, such as journals, magazines, and newspapers. They are also often referred to as serials. Periodicals usually consist of a collection of articles, which may range from a single page story in a magazine to a 40 page study in a scholarly journal.
Recently, knowledge discovery in large data increases its importance in various fields. Especially, data mining from time-series data gains much attention. This paper studies the problem of finding frequent episodes appearing in a sequence of events. We propose an efficient depth-first search algorithm for mining frequent serial episodes in a given event sequence using the notion of right-minimal occurrences. Then, we present some techniques for speeding up the algorithm, namely, occurrence-deliver and tail-redundancy pruning. Finally, we ran experiments on real datasets to evaluate the usefulness of the proposed methods.