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Combining Business Intelligence with Semantic Web: Overview and Challenges

Laborie, Sébastien and Ravat, Franck and Song, Jiefu and Teste, Olivier Combining Business Intelligence with Semantic Web: Overview and Challenges. (2015) In: 33eme Congrès sur l'INFormatique des Organisations et Systemes d'Information et de Decision (INFORSID 2015), 26 May 2015 - 29 May 2015 (Biarritz, France).

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Abstract

Under today’s highly complex and dynamic business environment, external data (most often issued from web) need to be included in traditional On-Line Analytical Processing (OLAP) analysis so that decision-makers would be well-informed before making effective decision. Including external web data requires knowing the exact semantic meaning in order to use the right information at the right time. Semantic Web (SW) technologies allow semantically annotating data so that we can exchange several descriptions over web data, do reasoning over these descriptions and ensure interoperability between humans and systems. A combination of BI technologies with SW will both enhance BI analysis with web data and allow analyzing SW data through BI tools. In this paper, we firstly introduce basic concepts of the BI and SW domains. Then, we present recent research results using SW to enhance OLAP analysis. At last, we identify challenges requiring future research efforts to achieve a complete incorporation of BI with SW.

Item Type:Conference or Workshop Item (Paper)
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Université de Pau et des Pays de l'Adour - UPPA (FRANCE)
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Deposited By: IRIT IRIT
Deposited On:27 Sep 2016 11:53

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