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 envisage a conversational framework specifically devised for OLAP applications. The system converts natural language text in GPSJ (Generalized Projection, Selection and Join) queries. The approach relies on an ad-hoc grammar and a knowledge base storing multidimensional metadata and cubes values. In case of ambiguous or incomplete query description, the system is able to obtain the correct query either through automatic inference or through interactions with the user to disambiguate the text. Our tests show very promising results both in terms of effectiveness and efficiency.
Towards conversational OLAP
Francia M.;Gallinucci E.;Golfarelli M.
2020
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 envisage a conversational framework specifically devised for OLAP applications. The system converts natural language text in GPSJ (Generalized Projection, Selection and Join) queries. The approach relies on an ad-hoc grammar and a knowledge base storing multidimensional metadata and cubes values. In case of ambiguous or incomplete query description, the system is able to obtain the correct query either through automatic inference or through interactions with the user to disambiguate the text. Our tests show very promising results both in terms of effectiveness and efficiency.| File | Dimensione | Formato | |
|---|---|---|---|
|
paper1.pdf
accesso aperto
Tipo:
Versione (PDF) editoriale
Licenza:
Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY)
Dimensione
1.48 MB
Formato
Adobe PDF
|
1.48 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
