Probabilistic algorithm for mining frequent sequences

The Probabilistic Algorithm for Mining Frequent Sequences

The subject of the paper is to analyze the problem of the frequency of the subsequences in large volume sequences (texts, databases, etc.). A new algorithm ProMFS for mining frequent sequences is proposed. It is based on the estimated probabilistic-statistical characteristics of the appearance of elements of the sequence and their order. The algorithm builds a new much shorter sequence and make...

A GSP-based Efficient Algorithm for Mining Frequent Sequences

ClaSP: An Efficient Algorithm for Mining Frequent Closed Sequences

In this paper, we propose a new algorithm, called ClaSP for mining frequent closed sequential patterns in temporal transaction data. Our algorithm uses several efficient search space pruning methods together with a vertical database layout. Experiments on both synthetic and real datasets show that ClaSP outperforms currently well known state of the art methods, such as CloSpan.

High Fuzzy Utility Based Frequent Patterns Mining Approach for Mobile Web Services Sequences

Nowadays high fuzzy utility based pattern mining is an emerging topic in data mining. It refers to discover all patterns having a high utility meeting a user-specified minimum high utility threshold. It comprises extracting patterns which are highly accessed in mobile web service sequences. Different from the traditional fuzzy approach, high fuzzy utility mining considers not only counts of mob...

PROWL: An Efficient Frequent continuity Mining Algorithm on Event Sequences

Mining association rule in event sequences is an important data mining problem with many applications. Most of previous studies on association rules are on mining intra-transaction association, which consider only relationship among the item in the same transaction. However, intra-transaction association rules are not a suitable for trend prediction. Therefore, inter-transaction association is ...