The Stanford Institute for Human-Centered AI published its 2025 AI Index report this week, providing a comprehensive look at the global state of Artificial Intelligence (AI). The report, now in its eighth edition, tracks and visualises data on technical performance, economic impact, education, policy, and responsible AI to offer an empirical foundation for understanding the field’s […]
Abstract: Academia and industry share a complex, multifaceted, and symbiotic relationship. Analysing the knowledge flow between them, understanding which directions have the biggest potential, and discovering the best strategies to harmonise their efforts is a critical task for several stakeholders. While research publications and patents are an ideal media to analyse this space, current datasets […]
ABSTRACT: Understanding, monitoring, and predicting the flow of knowledge between academia and industry is of critical importance for a variety of stakeholders, including researchers, policymakers, institutional funding bodies, companies operating in the innovation space and others. To this purpose, we introduce ResearchFlow, an approach for quantifying the evolution of research topics across academia and industry. […]
Last week, Angelo was in Oslo for the 23rd edition of the International Conference on Theory and Practice of Digital Libraries (TPDL2019). Every year, this conference attracts many researchers from all over the world, working in the fields of digital libraries, information retrieval, text analysis, web archives, and many others. Angelo attended the conference to present […]
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 environment. In this repository, we present the CSO Classifier, a new unsupervised approach for automatically classifying research papers according […]
We are pleased to announce that we recently created a new release of the CSO Classifier (v2.1), an application for automatically classifying research papers according to the Computer Science Ontology (CSO). Recently, we have been intensively working on improving its scalability, removing all its bottlenecks and making sure it could be run on large corpus. […]
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 environment. In this page, we present the CSO Classifier, a new unsupervised approach for automatically classifying research papers according […]
Scholarly Knowledge Mining
Digital Humanities
Data Science
Smart Cities and Robotics
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