Despite the presence of many systems for developing and managing structured taxonomies and/or SKOS models for a given domain for which small documents set are accessible, the production and maintenance of these domain knowledge bases is still a very expensive and time consuming process. This paper proposes a solution for assisting expert users in the development and management of knowledge base, including SKOS and ontologies modeling structures and relationships. The proposed solution accelerates the knowledge production by crawling and exploiting different kinds of sources (in multiple languages and with several inconsistencies among them). The proposed tool supports the experts in defining relationships among the most recurrent concepts, reducing the time to SKOS production and allowing assisted production. The validity of the produced knowledge base has been assessed by using SPARQL query interface and a precision and recall model. The solution has been developed for Open Space Innovative Mind project, with the aim of creating a portal to allow industries at posing semantic queries to discover potential competences in a large institution such as the University of Florence, in which several distinct domains are associated with its own departments.

Assisted Knowledge Base Generation, Management and Competence Retrieval

Andrea Bellandi;
2012

Abstract

Despite the presence of many systems for developing and managing structured taxonomies and/or SKOS models for a given domain for which small documents set are accessible, the production and maintenance of these domain knowledge bases is still a very expensive and time consuming process. This paper proposes a solution for assisting expert users in the development and management of knowledge base, including SKOS and ontologies modeling structures and relationships. The proposed solution accelerates the knowledge production by crawling and exploiting different kinds of sources (in multiple languages and with several inconsistencies among them). The proposed tool supports the experts in defining relationships among the most recurrent concepts, reducing the time to SKOS production and allowing assisted production. The validity of the produced knowledge base has been assessed by using SPARQL query interface and a precision and recall model. The solution has been developed for Open Space Innovative Mind project, with the aim of creating a portal to allow industries at posing semantic queries to discover potential competences in a large institution such as the University of Florence, in which several distinct domains are associated with its own departments.
Campo DC Valore Lingua
dc.authority.ancejournal INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING -
dc.authority.people Andrea Bellandi it
dc.authority.people Pierfrancesco Bellini it
dc.authority.people Antonio Cappuccio it
dc.authority.people Paolo Nesi it
dc.authority.people Gianni Pantaleo it
dc.authority.people Nadia Rauch it
dc.collection.id.s b3f88f24-048a-4e43-8ab1-6697b90e068e *
dc.collection.name 01.01 Articolo in rivista *
dc.contributor.appartenenza Istituto di linguistica computazionale "Antonio Zampolli" - ILC *
dc.contributor.appartenenza.mi 918 *
dc.date.accessioned 2024/02/17 15:40:00 -
dc.date.available 2024/02/17 15:40:00 -
dc.date.issued 2012 -
dc.description.abstracteng Despite the presence of many systems for developing and managing structured taxonomies and/or SKOS models for a given domain for which small documents set are accessible, the production and maintenance of these domain knowledge bases is still a very expensive and time consuming process. This paper proposes a solution for assisting expert users in the development and management of knowledge base, including SKOS and ontologies modeling structures and relationships. The proposed solution accelerates the knowledge production by crawling and exploiting different kinds of sources (in multiple languages and with several inconsistencies among them). The proposed tool supports the experts in defining relationships among the most recurrent concepts, reducing the time to SKOS production and allowing assisted production. The validity of the produced knowledge base has been assessed by using SPARQL query interface and a precision and recall model. The solution has been developed for Open Space Innovative Mind project, with the aim of creating a portal to allow industries at posing semantic queries to discover potential competences in a large institution such as the University of Florence, in which several distinct domains are associated with its own departments. -
dc.description.affiliations Distributed Systems and Internet Technology, Department of Systems and Informatics, University of Florence, Firenze, Italy -
dc.description.allpeople Andrea Bellandi; Pierfrancesco Bellini; Antonio Cappuccio; Paolo Nesi; Gianni Pantaleo; Nadia Rauch -
dc.description.allpeopleoriginal Andrea Bellandi, Pierfrancesco Bellini, Antonio Cappuccio, Paolo Nesi, Gianni Pantaleo, Nadia Rauch -
dc.description.fulltext none en
dc.description.numberofauthors 1 -
dc.identifier.uri https://hdl.handle.net/20.500.14243/19539 -
dc.language.iso eng -
dc.subject.keywords Semantic Web -
dc.subject.keywords Skills Management System -
dc.subject.keywords knowledge management -
dc.subject.keywords semantic queries -
dc.subject.keywords validation -
dc.subject.singlekeyword Semantic Web *
dc.subject.singlekeyword Skills Management System *
dc.subject.singlekeyword knowledge management *
dc.subject.singlekeyword semantic queries *
dc.subject.singlekeyword validation *
dc.title Assisted Knowledge Base Generation, Management and Competence Retrieval en
dc.type.driver info:eu-repo/semantics/article -
dc.type.full 01 Contributo su Rivista::01.01 Articolo in rivista it
dc.type.miur 262 -
dc.type.referee Sì, ma tipo non specificato -
dc.ugov.descaux1 271339 -
iris.orcid.lastModifiedDate 2024/03/02 01:54:28 *
iris.orcid.lastModifiedMillisecond 1709340868470 *
iris.sitodocente.maxattempts 1 -
Appare nelle tipologie: 01.01 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/19539
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