We present D-HOTM, a framework for Distributed Higher Order Text Mining based on named entities extracted from textual data that are stored in distributed relational databases. Unl...
Both full-text information retrieval and large scale parsing require text preprocessing to identify strong lexical associations in textual databases. In order to associate linguis...
As data mining techniques are being increasingly applied to non-traditional domains, existing approaches for finding frequent itemsets cannot be used as they cannot model the req...
Abstract. We consider the class of applications that manage time series (TS) and propose a data model and a query language that let these applications manipulate TS data sets at a ...
Abstract. In this paper, we propose a novel mining task: mining frequent superset from the database of itemsets that is useful in bioinformatics, e-learning systems, jobshop schedu...