activity
20182026
most citedGenerating Knowledge Graphs by Employing Natural Language Processing and Machine Learning Techniques within the Scholarly Domain

106 citations · 399 across the 16 of their papers we have counts for

collaborators

17 papers

cs.DL2026

COCI: Conference Organisers and Content Identifier

Angelo Salatino, Francesco Osborne, Alexis Vizcaino +2

Despite the critical role of grey literature in scholarly communication, artefacts such as Calls for Papers (CfPs) remain largely isolated from modern Scholarly Knowledge Graphs. T…

cs.DL2026

A Pathway for Assessing Grey Literature: Leveraging AI to Extract Conference Metadata and Organiser Information from Calls for Papers

Angelo Salatino, Francesco Osborne, Alexis Vizcaino +2

Despite its importance, grey literature, including Calls for Papers (CfPs), remains largely overlooked in Metascience and Scientometric analysis due to its unstructured, highly het…

cs.DL2024★ 12 cited

A Survey on Knowledge Organization Systems of Research Fields: Resources and Challenges

Angelo Salatino, Tanay Aggarwal, Andrea Mannocci +2

Knowledge Organization Systems (KOSs), such as term lists, thesauri, taxonomies, and ontologies, play a fundamental role in categorising, managing, and retrieving information. In t…

cs.AI2024★ 15 cited

Artificial Intelligence for Literature Reviews: Opportunities and Challenges

Francisco Bolanos, Angelo Salatino, Francesco Osborne +1

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 th…

cs.DL2023

Diversity of Expertise is Key to Scientific Impact: a Large-Scale Analysis in the Field of Computer Science

Angelo Salatino, Simone Angioni, Francesco Osborne +2

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 scienc…

cs.AI2023★ 6 cited

Knowledge Graphs: Opportunities and Challenges

Ciyuan Peng, Feng Xia, Mehdi Naseriparsa +1

With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately. As…

cs.AI2022★ 7 cited

Characterising Research Areas in the field of AI

Alessandra Belfiore, Angelo Salatino, Francesco Osborne

Interest in Artificial Intelligence (AI) continues to grow rapidly, hence it is crucial to support researchers and organisations in understanding where AI research is heading. In t…

cs.AI2021★ 61 cited

Trans4E: Link Prediction on Scholarly Knowledge Graphs

Mojtaba Nayyeri, Gokce Muge Cil, Sahar Vahdati +8

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…

cs.DL2021

Detection, Analysis, and Prediction of Research Topics with Scientific Knowledge Graphs

Angelo Salatino, Andrea Mannocci, Francesco Osborne

Analysing research trends and predicting their impact on academia and industry is crucial to gain a deeper understanding of the advances in a research field and to inform critical…

cs.IR2021★ 75 cited

The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articles

Angelo A. Salatino, Francesco Osborne, Thiviyan Thanapalasingam +1

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 o…

cs.DL2021★ 22 cited

Improving Editorial Workflow and Metadata Quality at Springer Nature

Angelo A. Salatino, Francesco Osborne, Aliaksandr Birukou +1

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 deter…

cs.DL2021★ 23 cited

Ontology-Based Recommendation of Editorial Products

Thiviyan Thanapalasingam, Francesco Osborne, Aliaksandr Birukou +1

Major academic publishers need to be able to analyse their vast catalogue of products and select the best items to be marketed in scientific venues. This is a complex exercise that…

cs.CL2020★ 106 cited

Generating Knowledge Graphs by Employing Natural Language Processing and Machine Learning Techniques within the Scholarly Domain

Danilo Dessì, Francesco Osborne, Diego Reforgiato Recupero +2

The continuous growth of scientific literature brings innovations and, at the same time, raises new challenges. One of them is related to the fact that its analysis has become diff…

cs.DL2020

Ontology Extraction and Usage in the Scholarly Knowledge Domain

Angelo A. Salatino, Francesco Osborne, Enrico Motta

Ontologies of research areas have been proven to be useful in many application for analysing and making sense of scholarly data. In this chapter, we present the Computer Science On…

cs.SE2019★ 1 cited

Reducing the Effort for Systematic Reviews in Software Engineering

Francesco Osborne, Henry Muccini, Patricia Lago +1

Context. Systematic Reviews (SRs) are means for collecting and synthesizing evidence from the identification and analysis of relevant studies from multiple sources. To this aim, th…

cs.HC2019★ 69 cited

The Evolution of IJHCS and CHI: A Quantitative Analysis

Andrea Mannocci, Francesco Osborne, Enrico Motta

In this paper we focus on the International Journal of Human-Computer Studies (IJHCS) as a domain of analysis, to gain insights about its evolution in the past 50 years and what th…

cs.SE2018★ 2 cited

The History of Software Architecture - In the Eye of the Practitioner

Henry Muccini, Patricia Lago, Karthik Vaidyanathan +2

Software architecture (SA) is celebrating 25 years. This is so if we consider the seminal papers establishing SA as a distinct discipline and scientific publications that have iden…