Since counterexamples generated by model checking tools are only symptoms of faults in the model, a significant amount of manual work is required in order to locate the fault that...
Constraints are essential for many sequential pattern mining applications. However, there is no systematic study on constraint-based sequential pattern mining. In this paper, we in...
Although there have been many recent studies on the mining of sequential patterns in a static database and in a database with increasing data, these works, in general, do not fully...
Sequential pattern mining is an important data mining method with broad applications that can extract frequent sequences while maintaining their order. However, it is important to ...
Classic algorithms for sequential pattern discovery, return all frequent sequences present in a database. Since, in general, only a few ones are interesting from a user's poin...
In sequential pattern discovery, the support of a sequence is computed as the number of data-sequences satisfying a pattern with respect to the total number of data-sequences in th...
Searching data streams has been traditionally very limited, either in the complexity of the search or in the size of the searched dataset. In this paper, we investigate the design...
Over the years, a variety of algorithms for finding frequent sequential patterns in very large sequential databases have been developed. The key feature in most of these algorith...
Sequential pattern mining has been studied extensively in data mining community. Most previous studies require the specification of a minimum support threshold to perform the min...
In this paper, we deal with mining sequential patterns in multiple data streams. Building on a state-of-the-art sequential pattern mining algorithm PrefixSpan for mining transact...