On the generation of useful linguistic summaries of sequences

Linguistic summarization techniques make it easy to gain insight into large amounts of data by describing the main properties of the data linguistically. In this paper we focus on a specific type of data, namely process data, i.e., event logs that contain information about when some activities were performed for a particular customer case. An event log may contain many different sequences, because actions or events are often performed in slightly different orders for different customer cases. This easily leads to a very large number of generated summaries. As the point of linguistic summarization is to provide a quick overview, such a large number of summaries is not helpful to the interpreter. To address this problem, we propose a method for the generation of linguistic summaries of sequences that groups similar sequences and returns them in a single linguistic summary. We show the applicability of our technique on an event log from practice and show that it can be used to reduce the number of produced summaries by 80%, while keeping the important information that is contained in those summaries.