Modern corporate performance management (CPM) systems are crucial tools for enterprises, but they typically lack a seamless integration with solutions in the Industry 4.0 domain for the exploitation of large amounts of data originated outside the enterprise boundaries. In this paper, we propose a solution to this problem, according to lessons learned in the development of project “Sibilla,” aimed at devising innovative tools in the business intelligence area. A proper software module is introduced with the purpose of enriching existing predictive analysis models with knowledge extracted from the Web and social networks. In particular, we describe how to support two functionalities: identification of planned real-world events and monitoring of public opinion on topics of interest to the company. The effectiveness of the proposed solution has been evaluated by means of a long-term experimental campaign.
Integration of web-scraped data in cpm tools: The case of project Sibilla
Bechini A.;Lazzerini B.;Marcelloni F.;Renda A.
2020-01-01
Abstract
Modern corporate performance management (CPM) systems are crucial tools for enterprises, but they typically lack a seamless integration with solutions in the Industry 4.0 domain for the exploitation of large amounts of data originated outside the enterprise boundaries. In this paper, we propose a solution to this problem, according to lessons learned in the development of project “Sibilla,” aimed at devising innovative tools in the business intelligence area. A proper software module is introduced with the purpose of enriching existing predictive analysis models with knowledge extracted from the Web and social networks. In particular, we describe how to support two functionalities: identification of planned real-world events and monitoring of public opinion on topics of interest to the company. The effectiveness of the proposed solution has been evaluated by means of a long-term experimental campaign.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.