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...
Local pattern mining algorithms generate sets of patterns, which are typically not directly useful and have to be further processed before actual application or interpretation. Ra...
This paper studies the problem of mining relational data hidden in natural language text. In particular, it approaches the relation classification problem with the strategy of tra...
Scientific bibliographies in online databases provide a rich source of information for scientists in support of their research. In this paper, we propose a new method to predict po...
The focus of this paper is to develop algorithms and a framework for modeling transactional data stored in relational database into graphs for mining. Most of the real-world trans...