SLOD-BI: An Open Data Infrastructure for Enabling Social Business Intelligence

Rafael Berlanga, Lisette García-Moya, Victoria Nebot, María José Aramburu, Ismael Sanz and Dolores María Llidó
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Rafael Berlanga: Universitat Jaume I, Castellón de la Plana, Spain
Lisette García-Moya: Universitat Jaume I, Castellón de la Plana, Spain
Victoria Nebot: Universitat Jaume I, Castellón de la Plana, Spain
María José Aramburu: Universitat Jaume I, Castellón de la Plana, Spain
Ismael Sanz: Universitat Jaume I, Castellón de la Plana, Spain
Dolores María Llidó: Universitat Jaume I, Castellón de la Plana, Spain

International Journal of Data Warehousing and Mining (IJDWM), 2015, vol. 11, issue 4, 1-28

Abstract: The tremendous popularity of web-based social media is attracting the attention of the industry to take profit from the massive availability of sentiment data, which is considered of a high value for Business Intelligence (BI). So far, BI has been mainly concerned with corporate data with little or null attention to the external world. However, for BI analysts, taking into account the Voice of the Customer (VoC) and the Voice of the Market (VoM) is crucial to put in context the results of their analyses. Recent advances in Sentiment Analysis have made possible to effectively extract and summarize sentiment data from these massive social media. As a consequence, VoC and VoM can be now listened from web-based social media (e.g., blogs, reviews forums, social networks, and so on). However, new challenges arise when attempting to integrate traditional corporate data and external sentiment data. This paper deals with these issues and proposes a novel semantic data infrastructure for BI aimed at providing new opportunities for integrating traditional and social BI. This infrastructure follows the principles of the Linked Open Data initiative.

Date: 2015
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