Inferring multidimensional cubes for representing conceptual document spaces

Authors:
Roxana Danger;Rafael Berlanga
Affiliations:
Departament de Llenguatges i Sistemes Informàtics, Universitat Jaume I, Castelló, Spain;Departament de Llenguatges i Sistemes Informàtics, Universitat Jaume I, Castelló, Spain
Venue:
CAEPIA'05 Proceedings of the 11th Spanish association conference on Current Topics in Artificial Intelligence
Year:
2005

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Abstract

This paper proposes a new method for representing document collections with conceptual multidimensional spaces inferred from their contents. Such spaces are built from a set of interesting word co-occurrences, which are properly arranged into taxonomies to define orthogonal hierarchical dimensions. As a result, users can explore and analyze the contents of large document collections by making use of well-known OLAP operators (On-Line Analytic Processing) over these spaces.