4.7 Article

An associative engines based approach supporting collaborative analytics in the Internet of cultural things

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.future.2016.04.015

Keywords

Cultural Heritage; Big Data; Business Intelligence; Internet of Things; Semantic technologies; Social networks

Funding

  1. National Research Foundation of Korea (NRF) grant - Korea government (MSIP) [NRF-2014R1A2A2A05007154]
  2. National Research Foundation of Korea [2014R1A2A2A05007154] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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In this paper we illustrate an integrated approach combining Business Intelligence, Big Data and Internet of Things (IoT), which is applied to information resources including structured and unstructured contents, Geo-Spatial and Social Network data, Multimedia (MM), multiple domain vocabularies, classifiers and ontologies. This is implemented in an information system which exploits Associative in-memory technologies in the context of Cloud Computing, as well as Semantic technologies for merging and analyzing information coming from heterogeneous sources. The primary aim is supporting Cultural Heritage Asset crowdsourcing, promotion, publication, management and usage. We describe and discuss, in particular, the application of this system for the analysis of behavior and interest of visitors in different types of populations and visits: on-site/ad-hoc (exhibitions, museums, cultural events) and territorial (historical downtown, archaeological or other touristic areas and routes including cultural resources). In this way it will be possible to provide a common ICT infrastructure and a set of advanced services for all types of subjects interested in the Cultural Heritage domain. The results of the experimentation encourage a Business Intelligence approach which is suitable for both nonprofit, research and business oriented organizations. (C) 2016 Elsevier B.V. All rights reserved.

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