The issue addressed in this paper concerns the discovery of frequent multi-dimensional patterns from relational sequences. The great variety of applications of sequential pattern m...
Floriana Esposito, Nicola Di Mauro, Teresa Maria A...
Abstract. In this paper, we present a theoretical foundation for querying inductive databases, which can accommodate disparate mining tasks. We present a data mining algebra includ...
This paper presents SaM, a split and merge algorithm for frequent item set mining. Its distinguishing qualities are an exceptionally simple algorithm and data structure, which not ...
Many interesting analyses for constraint logic-based languages are aimed at the detection of monotonic properties, that is to say, properties that are preserved as the computation...
Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mini...