Zobrazeno 1 - 10
of 237
pro vyhledávání: '"Marcel, Patrick"'
We introduce a conceptual model for highlights to support data analysis and storytelling in the domain of Business Intelligence, via the automated extraction, representation, and exploitation of highlights revealing key facts that are hidden in the d
Externí odkaz:
http://arxiv.org/abs/2403.00981
This vision paper lays the preliminary foundations for Data Narrative Management Systems (DNMS), systems that enable the storage, sharing, and manipulation of data narratives. We motivate the need for such formal foundations and introduce a simple lo
Externí odkaz:
http://arxiv.org/abs/2303.17141
Autor:
Gkitsakis, Dimos, Kaloudis, Spyridon, Mouselli, Eirini, Peralta, Veronika, Marcel, Patrick, Vassiliadis, Panos
In this paper, we discuss methods to assess the interestingness of a query in an environment of data cubes. We assume a hierarchical multidimensional database, storing data cubes and level hierarchies. We start with a comprehensive review of related
Externí odkaz:
http://arxiv.org/abs/2212.03294
The importance of context in data quality (DQ) was shown many years ago and nowadays is widely accepted. Early approaches and surveys defined DQ as \textit{fitness for use} and showed the influence of context on DQ. This paper presents a Systematic L
Externí odkaz:
http://arxiv.org/abs/2204.10655
Autor:
Gkitsakis, Dimos, Kaloudis, Spyridon, Mouselli, Eirini, Peralta, Veronika, Marcel, Patrick, Vassiliadis, Panos
Publikováno v:
In Information Systems July 2024 123
Publikováno v:
In Information Systems March 2024 121
This paper addresses the problem of defining a subjective interestingness measure for BI exploration. Such a measure involves prior modeling of the belief of the user. The complexity of this problem lies in the impossibility to ask the user about the
Externí odkaz:
http://arxiv.org/abs/1907.06946
This paper presents a proposal aiming at better understanding a workload of SQL queries and detecting coherent explorations hidden within the workload. In particular, our work investigates SQLShare [11], a database-as-a-service platform targeting sci
Externí odkaz:
http://arxiv.org/abs/1907.05618
Publikováno v:
Information Systems, volume 85, November 2019. pp. 68-91, ISSN 0306-4379
This paper structures a novel vision for OLAP by fundamentally redefining several of the pillars on which OLAP has been based for the last 20 years. We redefine OLAP queries, in order to move to higher degrees of abstraction from roll-up's and drill-
Externí odkaz:
http://arxiv.org/abs/1812.07854