Giacomo Di Tollo
Biographic Data
| ID | 4457192 |
|---|---|
| NAME | Giacomo Di Tollo |
| GIVEN NAMES | Giacomo |
| FAMILY NAME | Di Tollo |
| SIGNATURE | DI TOLLO G |
| AFFILIATIONS | Marche Polytechnic University |
| ORCID | 0000-0001-7044-6014 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Biclustering sustainable local tourism systems by the Tabu search optimization algorithm
Tourism is nowadays fully acknowledged as a leading industry contributing to boost the economic development of a country. This growing recognition has led researchers and policy makers to increasingly focus their attention on all those concerns related to optimally detecting, promoting and supporting territorial areas with a high tourist vocation, i.e., Local Tourism Systems . In this work, we propose to apply the biclustering data mining techniq…
Cultural heritage reuse applying fuzzy expert knowledge and machine learning: Venice’s fortresses case study
This paper presents a comparative analysis of two quantitative models for evaluating the reuse of cultural heritage, using fortified sites in a monofunctional city dedicated to cultural tourism, such as Venice, as a case study. The models explore three distinct reuse scenarios, assessing the appropriateness of each through a combination of fuzzy expert systems (FESs) and self-organising maps (SOMs). An FES acts as an expert-driven approach that f…
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Biclustering sustainable local tourism systems by the Tabu search optimization algorithm
Tourism is nowadays fully acknowledged as a leading industry contributing to boost the economic development of a country. This growing recognition has led researchers and policy makers to increasingly focus their attention on all those concerns related to optimally detecting, promoting and supporting territorial areas with a high tourist vocation, i.e., Local Tourism Systems . In this work, we propose to apply the biclustering data mining techniq…
Cultural heritage reuse applying fuzzy expert knowledge and machine learning: Venice’s fortresses case study
This paper presents a comparative analysis of two quantitative models for evaluating the reuse of cultural heritage, using fortified sites in a monofunctional city dedicated to cultural tourism, such as Venice, as a case study. The models explore three distinct reuse scenarios, assessing the appropriateness of each through a combination of fuzzy expert systems (FESs) and self-organising maps (SOMs). An FES acts as an expert-driven approach that f…
Artificial Intelligence (2 works) · Computer Science (2 works) · 3D Surveying and Cultural Heritage (1 works) · Algorithm (1 works) · Archaeology (1 works) · Architectural engineering (1 works) · Artificial Intelligence (1 works) · Biclustering (1 works) · Cluster analysis (1 works) · Cultural heritage (1 works)