Discovering unexpected and useful patterns in databases is a fundamental data mining task.
In recent years, a trend in data mining has been to design algorithms for discovering …

In this paper, we review recent progresses in the area of mining data from multiple data
sources. The advancement of information communication technology has generated a large …

We present SPMF, an open-source data mining library offering implementations of more
than 55 data mining algorithms. SPMF is a cross-platform library implemented in Java …

With the growing popularity of shared resources, large volumes of complex data of different
types are collected automatically. Traditional data mining algorithms generally have …

Sequential pattern mining algorithms using a vertical representation are the most efficient for
mining sequential patterns in dense or long sequences, and have excellent overall …

Sequential pattern mining is a computationally challenging task since algorithms have to
generate and/or test a combinatorially explosive number of intermediate subsequences. In …

Sequential pattern mining is a popular data mining task with wide applications. However, it
may present too many sequential patterns to users, which makes it difficult for users to …

Data Mining in general is the act of extracting interesting patterns and discovering non-trivial
knowledge from a large amount of data. Medical data mining can be used to understand the …

The problem of mining high utility sequences aims at discovering subsequences having a
high utility (importance) in a quantitative sequential database. This problem is a natural …

Sequential pattern mining (SPM) is an important technique in the field of pattern mining,
which has many applications in reality. Although many efficient SPM algorithms have been …