The democratization of data access and the adoption of OLAP in scenarios requiring hand-free interfaces push towards the creation of smart OLAP interfaces. In this paper, we describe COOL, a framework devised for COnversational OLap applications. COOL interprets and translates a natural language dialog into an OLAP session that starts with a GPSJ (Generalized Projection, Selection, and Join) query and continues with the application of OLAP operators. The interpretation relies on a formal grammar and on a repository storing metadata and values from a multidimensional cube. In case of ambiguous text description, COOL can obtain the correct query either through automatic inference or user interactions to disambiguate the text.

Conversational OLAP

Francia M.
;
Gallinucci E.;Golfarelli M.
2021

Abstract

The democratization of data access and the adoption of OLAP in scenarios requiring hand-free interfaces push towards the creation of smart OLAP interfaces. In this paper, we describe COOL, a framework devised for COnversational OLap applications. COOL interprets and translates a natural language dialog into an OLAP session that starts with a GPSJ (Generalized Projection, Selection, and Join) query and continues with the application of OLAP operators. The interpretation relies on a formal grammar and on a repository storing metadata and values from a multidimensional cube. In case of ambiguous text description, COOL can obtain the correct query either through automatic inference or user interactions to disambiguate the text.
CEUR Workshop Proceedings
403
410
Francia M.; Gallinucci E.; Golfarelli M.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/838877
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