We survey the current techniques to cope with the problem of string matching that allows
errors. This is becoming a more and more relevant issue for many fast growing areas such …

Sequences of events describing the behavior and actions of users or systems can be
collected in several domains. An episode is a collection of events that occur relatively close …

Discovering contrasts between collections of data is an important task in data mining. In this
paper, we introduce a new type of contrast pattern, called a Minimal Distinguishing …

Suppose one wants to detect bad or suspicious subsequences in event sequences. Whether
an observed pattern of activity (in the form of a particular subsequence) is significant and …

Sequence alignment remains a fundamental problem with practical applications ranging
from pattern recognition to computational biology. Traditional algorithms based on dynamic …

Fault management is an important but difficultarea of telecommunication network
management: networksproduce large amounts of alarm information which must beanalyzed …

Given two strings, the longest common subsequence (LCS) problem consists in computing
the length of the longest string that is a subsequence of both input strings. Its generalisation …

In this paper we address the task of summarizing a set of input sequences by means of local
ordering relationships on items occurring in the sequences. Our goal is not mining these …

Can we analyze data without decompressing it? As our data keeps growing, understanding
the time complexity of problems on compressed inputs, rather than in convenient …

Frequent episode discovery framework is a popular framework in temporal data mining with
many applications. Over the years, many different notions of frequencies of episodes have …