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Francesco Di Mauro

Researcher at University of Turin

Publications -  7
Citations -  30

Francesco Di Mauro is an academic researcher from University of Turin. The author has contributed to research in topics: Ontology (information science) & Computer science. The author has an hindex of 2, co-authored 6 publications receiving 21 citations.

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Smart ground project: A new approach to data accessibility and collection for raw materials and secondary raw materials in Europe

TL;DR: The Smart Ground project as discussed by the authors aims to facilitate the availability and accessibility of data and information on SRM in the EU, as well as creating synergy and collaboration between the different stakeholders involved in the SRM value chain.
Journal ArticleDOI

Matrix Factorization with Interval-Valued Data

TL;DR: This paper proposes matrix decomposition techniques that consider the existence of interval-valued data and shows that naive ways to deal with such imperfect data may introduce errors in analysis and present factorization techniques that are especially effective when the amount of imprecise information is large.
Proceedings ArticleDOI

Contextually-Enriched Querying of Integrated Data Sources

TL;DR: CrowdSourced Semantic Enrichment (CroSSE), a social knowledge platform supporting semantic enrichment and integrated services (such as content personalization, preview, and social recommendations) within the context of scientific investigations is presented.
Proceedings ArticleDOI

CrowdSourced semantic enrichment for participatory e-Government

TL;DR: This paper presents a novel participatory system which allows traditional databases and semantic tagging modules coexist in the same knowledge base, and provides the users with query enrichment functionalities to enable ontology-based query expansion.
Journal ArticleDOI

Crowd Sourced Semantic Enrichment (CroSSE) for knowledge driven querying of digital resources

TL;DR: CrowdSourced Semantic Enrichment (CroSSE) knowledge framework which allows traditional databases and semantic enrichment modules to coexist and provides a novel Semantically Enriched SQL (SESQL) language to enrich SQL queries with information from a knowledge base containing semantic annotations.