Supporting Editorial Activities at Springer Nature (2016-2019) – Co-PI and Technical Director. The project aims at fostering Springer Nature editorial activities by supporting them with a variety of smart solutions leveraging artificial intelligence, data mining, and semantic technologies. I led the research and development team in the creation of an array of approaches for i) classifying proceedings and other editorial products, ii) taking informed decisions about their marketing strategy, and iii) improve their internal classification. The project generated over £115K and produced two applications currently adopted by SN editors: the Smart Topic Miner, which helps editors to associate scholarly metadata to books; and the Smart Book Recommender, which assists editors in deciding which editorial products should be marketed in a specific venue.
MK:Smart (2014-2017) – Member. MK:Smart is a large collaborative initiative, partly funded by HEFCE (the Higher Education Funding Council for England) and led by The Open University, which is developing innovative solutions to support economic growth in Milton Keynes. I am working on the water package and supervising the developing the Garden Monitor App.
Rexplore (2012-2016) – Technical Director. The Rexplore project aim is to create a systems that leverages novel solutions in large-scale data mining, semantic technologies and visual analytics, to provide an innovative environment for exploring and making sense of scholarly data. This project gave rise to a number of tools and algorithms, such as Klink-2, a novel algorithm for ontology learning, Smart Topic Miner, a classifier used by Springer Nature, TechMiner, a tool for extracting technologies from research papers, and Research Community Map Builder, an algorithm for creating timelines of research communities.
PIEMONTE (2010-2013) – Member. The PIEMONTE project aimed to exploit smart-things for enhancing the interaction between people and cultural heritage. In the context of this project, I created OBUM, a novel recommender system which exploits ontology-based user models.
– Semantics, Analytics, Visualisation: Enhancing Scholarly Data Workshop (SAVE-SD) 2015-2018 at The Web Conference (WWW).
– Scientometrics Workshop (Scientometrics 2017) at ESWC
– Doctoral Consortium at EKAW 2018
Member of the program committees
– K-CAP 2018
– WWW 2017-2018
– ISWC 2016-2017
– ESWC 2017
– QEKGraph 2017
– SWM 2017
– Special issue of the Journal of Web Semantics on the topic of “Visualization and Interaction for Ontologies and Linked Data” 2017
– EKAW 2016-2018
– Drift-a-LOD 2016-2017
– BigScholar 2015-2017
– VOILA 2015-2017
– WOSP 2014-2017
– WLT 2014
Reviewer for International Journal of Human-Computer Studies, Sensors, Computing, HT 2012, UMAP 2013, ISWC 2014, K-CAP 2015, VOILA 2015, PRIVON 2015, STAIRS 2016, ISWC 2016.
Smart Book Recommender: A semantic application designed to support the Springer Nature editorial team in promoting their publications at Computer Science 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. It can also be used to find alternative conferences.
Refer to: Osborne, F., Thanapalasingam, T., Birukou, A. and Motta, E. (2017) Smart Book Recommender: A Semantic Recommendation Engine for Editorial Products, Poster at International Semantic Web Conference 2017
Smart Topic Miner: 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.
Refer to: Osborne, F., Salatino, A., Birukou, A., Motta, E. (2016) Automatic Classification of Springer Nature Proceedings with Smart Topic Miner. International Semantic Web Conference 2016, Kobe, Japan.
Garden Monitor: The Garden Monitor is a mobile application for Android, which supports efficient water management by generating a customized calendar advising users on whether and when they may need to water their garden over the following ten days. The application is able to learn the specific behaviour of a garden and forecast its future conditions by integrating data from weather forecasts, garden sensors, and personal and public weather stations.
Rexplore: A system which leverages novel solutions in large-scale data mining, semantic technologies and visual analytics, to provide an innovative environment for exploring and making sense of scholarly data. Rexplore does not rely on manually-generated taxonomies of research areas, which tend to be shallow and date very rapidly, but uses instead an innovative ontology population algorithm, Klink-2, which automatically constructs a semantic network of fine-grained research areas, linked by semantic relations.
Refer to: Osborne, F., Motta, E. and Mulholland, P. (2013) Exploring Scholarly Data with Rexplore, International Semantic Web Conference, Sydney, Australia.
OBUM: A tool for propagating user interest in ontology-based user models and proposing content-based recommendations.
Refer to: Cena, F., Likavec, S. and Osborne, F. (2013) Anisotropic propagation of user interests in ontology-based user models, Information Sciences. and Likavec, S., Osborne, F. and Cena, F. (2015) Property-based Semantic Similarity and Relatedness for Improving Recommendation Accuracy and Diversity. International Journal on Semantic Web and Information Systems (IJSWIS) 11, no. 4: 1-40.
CS-UDD: A system for discovering new attributes of a user by using the large amounts of public data present on Social Networks.
Refer to: Carmagnola, F., Osborne, F. and Torre, I. (2014) User data discovery and aggregation: The CS-UDD algorithm, Information Sciences, 270, 20, pp. 41-72, Elsevier
1st prize at the Semantic Publishing Challenge at the 2014 European Semantic Web Conference.
Finalist for the best paper award in ESWC 2014 and ICIDS 2011. Shortlisted for the best demo paper at ISWC 2016.