Contributions to conferences
2020 – Co-chair of “Science of Science” Track at ESWC.
2020 – Co-chair of the Scientific Knowledge Graph Workshop at TPDL.
2020 – Co-chair of Reframing Research (RefResh) Workshop at SOCINFO 2020
2019-2020 – Co-chair of Workshop on Deep Learning For Knowledge Graph (DL4KG) at ESWC.
2019 – Co-chair of “Research of Research” Track at ESWC.
2019 – Co-chair of Data Science special issue (extended papers of the SAVE-SD Workshop)
2018 – Co-chair of Doctoral consortium at EKAW 2018.
2018 – Co-chair of Reframing Research (RefResh) Workshop at EUROCSS Symposium.
2015-2018 – Co-chair of “Semantics, Analytics, Visualisation: Enhancing Scholarly Dissemination” Workshop (SAVE-SD 2015-2018 at WWW).
2017 – Co-chair of Scientometrics Workshop (Scientometrics 2017 at ESWC).
WOSP 2014, WLT 2014, WOSP 2015, BigScholar 2015, VOILA 2015, BigScholar 2016, WOSP 2016, ISWC P&D 2016, VOILA 2016, EKAW 2016, Drift-a-LOD 2016, SWM 2017, BigScholar 2017, VOILA 2017, WWW 2017, WOSP 2017, ESWC 2017, ISWC 2017, K-CAP 2017, QEKGraph 2017, Drift-a-LOD’18, RefResh 2018, VOILA 2018, WWW 2018, ESWC 2018, ISWC 2018, EKAW 2018, BigScholar 2018, DL4KG 2019, TheWebConf 2019, ESWC 2019, ISWC 2019, CLiC-it 2019, K-CAP 2019, AML 2019, SemEx 2019, CIKM 2020, JIST-KG 2020, ESWC 2020, ECAI 2020, ISWC 2020, EKAW 2020, SEMEX 2020, CLiC-it 2020, WOSP 2020, IRCDL 2021, TheWebConf 2021.
Journal of Web Semantics, Semantic Web journal, International Journal of Human-Computer Studies, Data Intelligence, Data Science, Future Generation of Computer Systems, PeerJ Computer Science, Information Processing and Management, MethodsX, Journal of Computational Science, EPJ Data Science, Knowledge and Information Systems.
2020 – Exploiting KMi’s scholarly analytics research to generate new sponsorship opportunities in Life Science – Co-PI and Technical Director. The main aim of this project is to support the migration of our scholarly analytics technologies to the Life Science domain, to open up new exploitation opportunities in this area.
2019-2020 – Intelligent technologies to support editorial strategies and marketing campaigns at Springer Nature – Co-PI and Technical Director. The project aims at developing novel intelligent technologies to automatically evaluate the quality of scientific conferences and inform editorial decisions. A significant outcome will be the development of novel technologies for characterising corporate clients according to their research interests, acquiring a better understanding of the relationship between academy and industry, and producing tailored packages of editorial products.
2018-2019 – Supporting Editorial Activities at Springer Nature – Co-PI and Technical Director. The project aimed at fostering Springer Nature editorial activities by supporting them with a variety of smart solutions leveraging artificial intelligence, data mining, and semantic technologies.
2016-2018 – Developing Semantic Technologies at Springer Nature – Co-PI and Technical Director. This project created Smart Topic Miner, the system which is now routinely used to assist Springer Nature editors in classifying conference proceedings, and Smart Book Recommender, an ontology-based recommender system for selecting the best editorial products to market at specific venues.
2014-2017 – Automatic Detection of Research Trends – Supervisor. This grant funded the PhD of Angelo Salatino, who developed a novel approach to forecasting the emergence of new research topics.
2014-2017 Rexplore – Technical Director. The project developed innovative services for exploring and making sense of scholarly data, using large-scale data mining, machine learning and semantic technologies. I led the research and development activities of the team working on the project.
2020-now Artificial Intelligence Knowledge Graph, AI-KG (http://w3id.org/aikg): It is a large-scale automatically-generated knowledge graph that describes 850K entities (e.g., tasks, methods, metrics, materials, others) relevant to AI according to 1,2M statements extracted from 333K articles.
2020-now Academia/Industry DynAmics Knowledge Graph, AIDA (http://w3id.org/aida): It is an innovative resource for supporting large-scale analyses of research trends across academia and industry. It describes 21M publications and 8M patents according to the research topics drawn from the Computer Science Ontology, the type of the author’s affiliations (e.g., academy, industry, collaborative), and 66 industrial sectors (e.g., automotive, financial, energy, electronics).
2019-now – CSO Classifier (https://github.com/angelosalatino/cso-classifier): It is an innovative unsupervised approach for automatically classifying research papers according to the Computer Science Ontology (CSO). The CSO Classifier takes as input the metadata associated with a research paper and returns a selection of research concepts drawn from the ontology. It is used by several universities and organizations for automatically annotating their research outputs.
2018-now – The Computer Science Ontology (CSO) (http://cso.kmi.open.ac.uk): CSO is a large-scale, open, automatically generated ontology of research areas. It is the largest taxonomy in the field of Computer Science, including about 14K topics and over 162K relationships. I produced it by applying my Klink-2 algorithm on a very large dataset of 16M scientific articles. CSO powers several tools adopted by the editorial team at Springer Nature and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends.
2017-now – Smart Book Recommender (http://skm.kmi.open.ac.uk/sbr/): A semantic application designed to support the Springer Nature editorial team in promoting their publications at CS venues. It takes as input the proceedings of a conference and suggests books, journals, and other conference proceedings which are likely to be relevant to the attendees of the conference in question.
2016-now – Smart Topic Miner (http://stm-demo.kmi.open.ac.uk/): A tool which uses semantic web technologies to classify scholarly publications on the basis of a very large automatically generated ontology of research areas. It was developed to support the Springer Nature Computer Science editorial team in classifying proceedings.
2015-2017 – Garden Monitor App (http://www.mksmart.org/gardenmonitor/): A mobile application that uses machine learning techniques for generating a customized calendar advising users on how to water their garden in the following ten days.
2012-2015 – Klink-2 (http://skm.kmi.open.ac.uk/klink-2): An application which takes as input large amounts of scholarly metadata and automatically generates an OWL ontology containing all the research areas mined from the input data and their semantic relationships.
2012-2017 – Rexplore (http://skm.kmi.open.ac.uk/rexplore): A system that provides an innovative environment for analysing the research landscape and the performance of scientists, universities and scientific communities.
- Best Paper Award at SAVE-SD 2018.
- 1st prize at the Semantic Publishing Challenge at the European Semantic Web Conference 2014.
- Best Paper Award Nominee at ISWC 2020 (Poster), ISWC 2019 (In-use), ISWC 2019 (Poster), ISWC 2019 (Demo), JCDL 2019, ISWC 2018 (Resources), ESWC 2014, and ICIDS 2011.
- DataIQ Award Nominee 2020
- Finalist at the Springer Nature Internal Innovation Competition 2020
- Best Project Award at SWSS 2011.