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Using Information Visualization to Support Open Data Integration Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Validation Approaches for a Biological Model Generation Describing Visitor Behaviours in a Cultural Heritage Scenario

Authors : Salvatore Cuomo, Pasquale De Michele, Giovanni Ponti, Maria Rosaria Posteraro

Published in: Data Management Technologies and Applications

Publisher: Springer International Publishing

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Abstract

In this paper we propose a biologically inspired mathematical model to simulate the personalized interactions of users with cultural heritage objects. The main idea is to measure the interests of a spectator w.r.t. an artwork by means of a model able to describe the behaviour dynamics. In this approach, the user is assimilated to a computational neuron, and its interests are deduced by counting potential spike trains, generated by external currents. The key idea of this paper consists in comparing a strengthened validation approach for neural networks based on classification with our novel proposal based on clustering; indeed, clustering allows to discover natural groups in the data, which are used to verify the neuronal response and to tune the computational model.
Preliminary experimental results, based on a phantom database and obtained from a real world scenario, are shown. They underline the accuracy improvements achieved by the clustering-based approach in supporting the tuning of the model parameters.

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Metadata
Title
Validation Approaches for a Biological Model Generation Describing Visitor Behaviours in a Cultural Heritage Scenario
Authors
Salvatore Cuomo
Pasquale De Michele
Giovanni Ponti
Maria Rosaria Posteraro
Copyright Year
2015
Book
Data Management Technologies and Applications

Print ISBN: 978-3-319-25935-2

Electronic ISBN: 978-3-319-25936-9

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-25936-9_10

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