DocumentCode :
682617
Title :
A PageRank based predictive model for the estimation of the archaeological potential of an urban area
Author :
Dubbini, Nevio ; Gattiglia, Gabriele
Author_Institution :
Math. Dept., Univ. of Pisa, Pisa, Italy
Volume :
1
fYear :
2013
fDate :
Oct. 28 2013-Nov. 1 2013
Firstpage :
571
Lastpage :
578
Abstract :
We present the analysis of multi-faceted, GIS managed data for determining the archaeological potential, i.e. a measure of the possibility that a more or less significant archaeological stratification is preserved. We used a sizable number of datasets, in order to consider the problem of estimation of archaeological potential in all of its aspects: archaeological data, building archaeological data, historical data, toponymic data, geomorphological data. As the identification of relations among finds is a key issue for the data mining in archaeological interpretation process, we applied a modified version of the PageRank model, because the criteria for assigning importance to web pages by search engines are similar and based on relations, also. The procedure included a categorization archaeological data, the assignment of initial values of potential to the available data through an automatic procedure, the creation of geomorphological facies maps, the definition of functional areas (i.e. the levels of spatial and functional organization: urban, suburban and rural areas), and the application of the PageRank based algorithm. The model has been applied on the urban area of Pisa, and tested through the data of 14 new cores. The map of archaeological potential consists of the composition of the 7 layers, one for each archaeological period under consideration: Protohistory, Etruscan period, Roman period, Late Roman period, Early Medieval period, Late Medieval period, Modern Age, Contemporary Age. The results, including the archaeological potential map, are to be considered as the first steps towards an automatic, formally definable, and repeatable, approach to the computation of archaeological potential.
Keywords :
archaeology; data mining; pattern classification; Contemporary Age; Early Medieval period; Etruscan period; Late Medieval period; Late Roman period; Modern Age; PageRank based predictive model; Pisa; Protohistory period; Roman period; archaelogical potential initial value assignment; archaeological data categorization; archaeological interpretation process; archaeological potential estimation; building archaeological data; data mining; functional area definition; geomorphological data; geomorphological facies maps; historical data; multifaceted GIS managed data; toponymic data; urban area; Buildings; Data models; Estimation; Geology; IEEE Potentials; Mathematical model; Shape; PageRank; archaeological GIS; archaeological potential; geomorphology; predictive modelling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Heritage International Congress (DigitalHeritage), 2013
Conference_Location :
Marseille
Print_ISBN :
978-1-4799-3168-2
Type :
conf
DOI :
10.1109/DigitalHeritage.2013.6743798
Filename :
6743798
Link To Document :
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