Tag Archives: Scholarly Knowledge Mining

AIDA: a Knowledge Graph about Research Dynamics in Academia and Industry

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 […]

AIDA: a Knowledge Graph about ResearchDynamics in Academia and Industry

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 […]

ResearchFlow: Understanding the Knowledge Flow between Academia and Industry

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. […]

Klink-2 among the top-cited ISWC papers in the past 5 years

We are extremely pleased to see that our paper about Klink-2 [1] is included in the list generated by Google Scholar (link), which presents the most cited papers published in the past 5 years at the International Semantic Web Conference (ISWC). This is the main international forum for showcasing the latest academic and industrial results […]

The CSO Classifier nominated for the Best Paper Award

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 […]

SMART TOPIC MINER – Improving Editorial Workflow and Metadata Quality at Springer Nature

Smart Topic Miner Smart Topic Miner (STM) is an application that assists the Springer Nature editorial team in classifying the scientific literature in Computer Science in terms of a catalogue of about 15K research topics, with a very high degree of accuracy. This catalogue was itself generated by our team using a highly innovative knowledge […]

CSO-Classifier available on PIP

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 […]

Angelo succeeds in his VIVA

Congratulations to Angelo Salatino for succeeding in his viva! On 31st May 2019, Angelo Salatino successfully defended his PhD thesis on Early Detection of Research Trends. The thesis is a body of research work over the last three years leading to a successful system that identifies the emergence of new research topics up to two […]

New release: CSO Classifier v2.1

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. […]

CSO Classifier

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 […]