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

“AIDA: a Knowledge Graph about Research Dynamics in Academia and Industry” is a research paper published at the Special Issue on “Scientific Knowledge Graphs and Research Impact Assessment” at Quantitative Science Studies (QSS by MIT Press). Simone Angioni1, Angelo Antonio Salatino2, Francesco Osborne2, Diego Reforgiato Recupero1, Enrico Motta2 1 Department of Mathematics and Computer Science, University […]

Read More

Assessing Scientific Conferences through Knowledge Graphs

“Assessing Scientific Conferences through Knowledge Graphs” is a paper published at the Industry Track of the 2021 International Semantic Web Conference. Simone Angioni1, Angelo Antonio Salatino2, Francesco Osborne2, Aliaksandr Birukou3, Diego Reforgiato Recupero1, Enrico Motta2 1 Department of Mathematics and Computer Science, University of Cagliari (Italy) 2 Knowledge Media Institute, The Open University, Milton Keynes (UK) […]

Read More

AIDA-Bot: A Conversational Agent to ExploreScholarly Knowledge Graphs

“AIDA-Bot: A Conversational Agent to ExploreScholarly Knowledge Graphs” is a demo paper accepted for presentation at the International Semantic Web Conference (ISWC 2021) poster and demo session. Antonello Meloni1, Simone Angioni1, Angelo Antonio Salatino2, Francesco Osborne2, Diego Reforgiato Recupero1, Enrico Motta2 1 Department of Mathematics and Computer Science, University of Cagliari (Italy) 2 Knowledge Media […]

Read More

RDF Schema of research articles in the Academia/Industry DynAmics (AIDA) Knowledge Graph

Link Prediction of Weighted Triples for Knowledge Graph Completion Within the Scholarly Domain

“Link Prediction of Weighted Triples for Knowledge Graph Completion Within the Scholarly Domain” is a journal paper accepted at IEEE Access Mojtaba Nayyeri1,2, Gökce Müge Cil1, Sahar Vahdati2, Francesco Osborne3, Andrey Kravchenko4, Simone Angioni5, Angelo Salatino3, Diego Reforgiato Recupero5, Enrico Motta3, Jens Lehmann1,6   1 SDA Research Group, University of Bonn, 53115 Bonn, Germany 2 […]

Read More

CSO Classifier 3.0

Abstract 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 […]

Read More

CSO Classifier 3.0: A Scalable Unsupervised Method for Classifying Documents in Terms of Research Topics

“CSO Classifier 3.0: A Scalable Unsupervised Method for Classifying Documents in Terms of Research Topics” is a journal paper accepted at the Special Issue of “TPDL 2019 & 2020” at Scientometrics. Angelo Salatino, Francesco Osborne, Enrico Motta Abstract Classifying scientific articles, patents, and other documents according to the relevant research topics is an important task, […]

Read More

Trans4E: Link Prediction on Scholarly Knowledge Graphs

“Trans4E: Link Prediction on Scholarly Knowledge Graphs” is a journal paper submitted to the Special Issue on “Knowledge Graph Representation & Reasoning” at the Neurocomputing Journal   Mojtaba Nayyeria, Gokce Muge Cila, Sahar Vahdatib, Francesco Osborned, Mahfuzur Rahmana,Simone Angionie, Angelo Salatinod, Diego Reforgiato Recuperoe, Nadezhda Vassilyevaa, Enrico Mottad and Jens Lehmanna,c aSDA Research Group, University […]

Read More

Clique Percolation Method in Python

Clique Percolation Method (CPM) is an algorithm for finding overlapping communities within networks, introduced by Palla et al. (2005, see references). This implementation in Python, firstly detects communities of size k, then creates a clique graph. Each community will be represented by each connected component in the clique graph. Algorithm The algorithm performs the following […]

Read More

AIDA Dashboard

The AIDA Dashboard is a web application that allows users to visualize several kind of analytics about a specific conference (see Figure 1). The backend is developed in Python, while the frontend is in HTML5 and Javascript. The AIDA Dashboard builds on the Academia/Industry DynAmics knowledge graph (AIDA), a large knowledge base describing 14M articles […]

Read More

ResearchFlow: Understanding the Knowledge Flow between Academia and Industry

“ResearchFlow: Understanding the Knowledge Flow between Academia and Industry” is a conference paper submitted to Knowledge Engineering and Knowledge Management – 22nd International Conference, EKAW 2020. Angelo Salatino, Francesco Osborne, Enrico Motta Abstract Understanding, monitoring, and predicting the flow of knowledge between academia and industry is of critical importance for a variety of stakeholders, including governments, funding […]

Read More