Title: A perspective on applications of in-memory and associative approaches supporting cultural big data analytics
Authors: Angelo Chianese; Francesco Piccialli
Addresses: Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy ' Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Naples, Italy
Abstract: Business intelligence, advanced analytics, big data, in-memory database and associative technologies are actually the key enablers for enhanced business decision making. In this paper, we provide a perspective on applications of in-memory approaches supporting analytics in the field of the cultural heritage applied to information resources including structured and unstructured contents, geo-spatial and social network data, multimedia (MM), multiple domain vocabularies, classifiers and ontologies. The proposed approach has been implemented in an information system exploiting associative in-memory technologies in a cloud context, as well as integrating semantic technologies for merging and analysing information coming from heterogeneous sources. We analyse and describe the application of this system to trace a behavioural and interest profile of users and visitors for cultural events (exhibitions, museums, etc.) and territorial (tourist areas and routes including cultural resources, historical down-town, and archaeological sites). The results of ongoing experimentation encourage a business intelligence approach which is suitable for supporting cultural heritage asset crowdsourcing, promotion, publication, management and usage.
Keywords: in-memory database systems; big data; social analytics; business intelligence; cultural heritage; internet of things; IoT.
International Journal of Computational Science and Engineering, 2018 Vol.16 No.3, pp.219 - 233
Received: 02 Feb 2016
Accepted: 11 Jun 2016
Published online: 03 May 2018 *