A perspective on applications of in-memory and associative approaches supporting cultural big data analytics
by Angelo Chianese; Francesco Piccialli
International Journal of Computational Science and Engineering (IJCSE), Vol. 16, No. 3, 2018

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.

Online publication date: Wed, 16-May-2018

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