id
	15352
Url
	https://chloe.cnr.it/s/BiDiAr/item/15352
Resource template
	Conference Paper
Resource class
	fabio:ConferencePaper
Title
	Encoding and Simulating the Past. A Machine Learning Approach to the Archaeological Information
Creator
	Ramazzotti, Marco
	Buscema, Paolo Massimo
	Massini, Giulia
	Torre, Francesca Della
Date
	2018
Language
	eng
Abstract
	The encoding of the spatial-temporal archeological, historical and anthropological records can be considered an ideal-typical representation of the human reasoning and thus also an artificial membrane interposed between the researcher and the past. These membranes are here considered artificial networks and can undergo interrogation processes through the most advanced analytical tools for learning and modeling complex configurations. The aim of this paper is to synthesize recent advances in Artificial Intelligence and Computer Science and - at the same time - to support the connectionists and symbolic computational paradigms as a new epistemic frontier in the automatic annotation of tangible and intangible heritage as well in the contemporary theories and methods of the archeological thought.
Is Part Of
	2018 Metrology for Archaeology and Cultural Heritage (MetroArchaeo)
Doi
	https://doi.org/10.1109/MetroArchaeo43810.2018.9089813
Pages
	39-44
Uri
	https://ieeexplore.ieee.org/document/9089813
Homepage
	https://www.zotero.org/groups/5293298/bidiar/items/SP9894EE/item-list

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