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pro vyhledávání: '"MOTTA, ENRICO"'
Ontologies of research topics are crucial for structuring scientific knowledge, enabling scientists to navigate vast amounts of research, and forming the backbone of intelligent systems such as search engines and recommendation systems. However, manu
Externí odkaz:
http://arxiv.org/abs/2412.08258
Knowledge Organization Systems (KOSs), such as term lists, thesauri, taxonomies, and ontologies, play a fundamental role in categorising, managing, and retrieving information. In the academic domain, KOSs are often adopted for representing research a
Externí odkaz:
http://arxiv.org/abs/2409.04432
This manuscript presents a comprehensive review of the use of Artificial Intelligence (AI) in Systematic Literature Reviews (SLRs). A SLR is a rigorous and organised methodology that assesses and integrates previous research on a given topic. Numerou
Externí odkaz:
http://arxiv.org/abs/2402.08565
Autor:
Salatino, Angelo, Angioni, Simone, Osborne, Francesco, Recupero, Diego Reforgiato, Motta, Enrico
Understanding the relationship between the composition of a research team and the potential impact of their research papers is crucial as it can steer the development of new science policies for improving the research enterprise. Numerous studies ass
Externí odkaz:
http://arxiv.org/abs/2306.15344
Autor:
Cadeddu, Andrea, Chessa, Alessandro, De Leo, Vincenzo, Fenu, Gianni, Motta, Enrico, Osborne, Francesco, Reforgiato Recupero, Diego, Salatino, Angelo, Secchi, Luca
Publikováno v:
In Engineering Applications of Artificial Intelligence July 2024 133 Part B
Autor:
Nayyeri, Mojtaba, Cil, Gokce Muge, Vahdati, Sahar, Osborne, Francesco, Rahman, Mahfuzur, Angioni, Simone, Salatino, Angelo, Recupero, Diego Reforgiato, Vassilyeva, Nadezhda, Motta, Enrico, Lehmann, Jens
The incompleteness of Knowledge Graphs (KGs) is a crucial issue affecting the quality of AI-based services. In the scholarly domain, KGs describing research publications typically lack important information, hindering our ability to analyse and predi
Externí odkaz:
http://arxiv.org/abs/2107.03297
Autor:
Fyrigos, Antonis
Publikováno v:
Gregorianum, 2005 Jan 01. 86(3), 708-709.
Externí odkaz:
https://www.jstor.org/stable/23582441
Publikováno v:
In Digital Libraries for Open Knowledge. LNCS, vol 11799. Springer, Cham (2019)
Classifying research papers according to their research topics is an important task to improve their retrievability, assist the creation of smart analytics, and support a variety of approaches for analysing and making sense of the research environmen
Externí odkaz:
http://arxiv.org/abs/2104.00948
Service robots are expected to reliably make sense of complex, fast-changing environments. From a cognitive standpoint, they need the appropriate reasoning capabilities and background knowledge required to exhibit human-like Visual Intelligence. In p
Externí odkaz:
http://arxiv.org/abs/2104.00387
Identifying the research topics that best describe the scope of a scientific publication is a crucial task for editors, in particular because the quality of these annotations determine how effectively users are able to discover the right content in o
Externí odkaz:
http://arxiv.org/abs/2103.13527