SKM3

SKM3
SKM3 – Modelling / Mining / Sense Making
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About
The SKM team aims to develop innovative approaches to generating value from scholarly data by leveraging artificial intelligence, large-scale data mining, semantic technologies, and visual analytics.
We are pursuing several research avenues, including:
AI systems for
automated literature reviews
hypothesis generation
citation prediction
, and
metascience
Generation of
knowledge graphs
, as well as their refinement through
automatic methods
and
human-in-the-loop approaches
Large-scale
classification
of scientific publications.
Our technologies also powered
Stanford’s AI Index
, the most well-known AI report.
Analysis and integration of
knowledge organization systems
of research fields, including the automatic
generation
and
evolution
of taxonomies
– see, for example, the
Computer Science Ontology
AI tools for exploring and analysing the scientific landscape – see, for example, the
AIDA Dashboard
Automatic forecasting of the
emergence of new research fields
We released a number of knowledge bases for exploring research dynamics, including:
The
Computer Science Ontology
(CSO), the largest taxonomy of research topics in the field.
The
Academia/Industry DynAmics
(AIDA) Knowledge Graph is an innovative resource that describes 14M publications and 8M patents according to their topics and industrial sectors.
The
Computer Science Knowledge Graph
(CS-KG), a large-scale automatically generated knowledge graph that describes 25M entities (e.g., tasks, methods, metrics, materials, others) extracted from 15M research publications.
We collaborate with
major publishers
and universities
to generate scalable applications, such as search engines, recommender systems, and analytics tools. In particular, we are currently working closely with Springer Nature in the development of several semantically enhanced solutions.
In 2019, we released the
Computer Science Ontology
(CSO), which is currently the largest taxonomy of research areas in the field and has been
officially
adopted
by Springer Nature
.  In the context of our collaboration with Springer Nature, I have also designed and co-developed the
Smart Topic Miner
, a tool is used by editors at Springer Nature to generate automatically the scholarly metadata for all their computer science proceedings, including flagship series, such as Lecture Notes in Computer Science (LNCS), Lecture Notes in Artificial Intelligence, and others.
In 2021, we generated the
Academia/Industry DynAmics
(AIDA) Knowledge Graph, an innovative resource for supporting large-scale analyses of research trends across academia and industry.  AIDA describes
14M publications and 8M patents
according to the research topics drawn from CSO, the type of the author’s affiliations (e.g., academy, industry, collaborative), and 66 industrial sectors (e.g., automotive, financial, energy, electronics). In 2022, we also produced the
Computer Science Knowledge Graph
(CS-KG), a large-scale automatically generated knowledge graph that describes
25M entities
(e.g., tasks, methods, metrics, materials, others) extracted from
15M articles
. CS-KG was designed to support a large variety of intelligent services for analysing and making sense of research dynamics, assisting researchers, and informing the decisions of founding bodies and research policymakers.
Recently, our work has focused on the
intersection of generative AI and knowledge graphs
, aiming to create advanced systems for scientific exploration, horizon scanning, research hypothesis generation, and the automated production of literature reviews. As part of this effort, we published an in-depth survey on the transformative impact of
AI systems for literature reviews
, providing key recommendations for future research.
News
SKM and Springer Nature Renew Their Partnership for another two years
We are very happy to announce that our team has secured a new two-year contract with Springer Nature (SN), which will continue the long-established strategic partnership until December 2027. This marks the continuation of an exceptional collaboration that has now spanned more than 11 years and represents a strong example of how academia and industry can work together to drive innovation and...
News
27 Nov 2025 11:08
Tracking Stars and Unicorns
KMi secured a new research project “Tracking Stars and Unicorns” funded by the UKRI Metascience unit, with an award of £310,646, to look at successful and unsuccessful proposals within all UKRI councils to track research trends, assess UK competitiveness against global competitors, and understand appropriate funding mechanisms to better support the development of Early Career...
News
09 Oct 2025 09:40
SKM nets UKRI grant to put AI in the grant-review driving seat
Dr. Francesco Osborne, from SKM, has secured ~£200,000 from UKRI’s Metascience Unit to explore how large language models can streamline grant peer review without diluting fairness. The 12-month project, in partnership with the CORE team at KMi, Sheffield and Salford universities, will test four AI roles: triaging low-quality proposals, acting as a third reviewer, synthesising opinions as a...
News
06 Oct 2025 09:44
SKM at Dagstuhl: Open Scholarly Information Systems
Last week, Dr Angelo Salatino attended an invited prestigious Dagstuhl Seminar addressing the status quo, opportunities, and challenges of Open Scholarly Information Systems. Over the last 30 years, a wide range of open scholarly information systems have been developed to serve the scientific community. The seminar has been attended by representatives of metadata aggregators like DBLP,...
News
22 Sep 2025 09:22
SKM’s report from SEMANTiCS 2025
The 21st edition of the International Conference on Semantic Systems, commonly known as SEMANTiCS, took place in Vienna last week. This yearly event brings together academics and industry professionals to transfer knowledge and advance innovation. Around 300 participants from across Europe and beyond attended SEMANTiCS 2025. Major themes discussed included various combinations of symbolic and...
News
08 Sep 2025 09:21
Angelo gives a webinar to ISKO UK Meetup
On 20 May 2025, Dr. Angelo Salatino was invited to give a webinar to the ISKO UK Meetup about our recently published survey "A Survey on Knowledge Organisation Systems of Research Fields: Resources and Challenges". ISKO UK Meetups are known for bringing together academics and practitioners to explore a wide range of practical and technology-oriented topics related to knowledge organisation...
News
25 May 2025 18:26
View All News Stories
Research and Development
The AIDA Dashboard
technology
The Conference Dashboard is a tool for exploring and making sense of scientific conferences which integrates statistical analysis, semantic technologies, and visual analytics. The dashboard was developed in collaboration with Springer Nature for assisting editors in assessing conferences, but it also supports several other use cases.
Smart Topic Miner 2 - Improving Editorial Workflow and Metadata Quality at Springer Nature
technology
Smart Topic Miner 2 (STM2) is a web application that assists editors at Springer Nature in classifying books and more in general any collection of research papers.
Project - Supporting editorial activities at Springer Nature
project
The Rexplore team and Springer Nature have launched a new research project with the aim of developing new innovative solutions to support editorial activity at Springer Nature. The project will be lead by Enrico Motta and Francesco Osborne and will start on May 2018.
CSO Classifier
technology
The CSO Classifier is a new unsupervised approach for automatically classifying research papers according to the Computer Science Ontology (CSO), a comprehensive ontology of research areas in the field of Computer Science.
Computer Science Ontology - the largest ontology of research topics
technology
The Computer Science Ontology (CSO) is a large-scale ontology of research areas that was automatically generated using the Klink-2 algorithm. The last version includes about 26k topics linked by 226k semantic relationships.
Augur - early forecasting of research trends
technology
Augur is a novel approach to the early detection of research topics. Augur analyses the diachronic relationships between research areas and is able to detect clusters of topics that exhibit dynamics correlated with the emergence of new research topics.
Technology-Topic Framework - forecasting technology propagation
technology
The Technology-Topic Framework (TTF) is a novel approach which uses a semantically enhanced technology-topic model to forecast the propagation of technologies to research areas.
Smart Topic Miner - classifying Springer Nature publications
technology
Smart Topic Miner (STM) is a web application which uses Semantic Web technologies to classify scholarly publications on the basis of Computer Science Ontology (CSO), a very large automatically generated ontology of research areas. It was developed to support the Springer Nature Computer Science editorial team in classifying proceedings in the LNCS family.
Smart Book Recommender - suggesting scientific books
technology
The Smart Book Recommender(SBR) is 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.
Rexplore - a environment for exploring research
technology
Rexplore is a system 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.
Klink-2 - automatic generation of research topic ontologies
technology
Klink-2 is 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. It was developed to produced large scale ontology of research topics.
People
Francesco
Osborne
Senior Research Fellow
Team Leader
Enrico
Motta
Professor of Knowledge Technologies
Angelo
Salatino
Research Fellow
Francisco
Bolaños Burgos
PhD Student
AI for Literature Review.
Tanay
Aggarwal
PhD Student
Generation of Research Areas Ontologies.
Michael
McCoubrey
Part-time PhD Student
AI System for Hypothesis Generation
Danilo
Dessì
Visiting Researcher
Knowledge Graph generation.
Alessia
Pisu
Visiting PhD Student
Generation of Research Areas Ontologies.
Vincenzo
De Leo
Visiting PhD Student
Knowledge Injection for LLM.
Antonello
Meloni
Visiting PhD Student
Conversational Agents.
Marco
Murgia
Visiting PhD Student
Citation prediction.
Massimiliano
Fadda
Visiting PhD Student
AI for analysing News Media.
Andrea
Ibba
Visiting PhD Student
Conversational Agents.
Resources
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...
Slides
28 Aug 2020 16:36
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 governments, funding bodies, researchers, investors, and companies. To this purpose, we introduce ResearchFlow, an approach that integrates semantic technologies and machine learning to quantifying the diachronic behaviour...
Slides
21 Mar 2020 10:10
The CSO Classifier: Ontology-Driven Detection of Research Topics in Scholarly Articles
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 paper, we present the CSO Classifier, a new unsupervised approach for automatically classifying research papers according to...
Data Ontology
25 Jan 2019 10:35
K-CAP 2017 SLIDES – Forecasting the Spreading of Technologies in Research Communities
Forecasting the Spreading of Technologies in Research Communities @ K-CAP 2017 from Francesco...
Slides
05 Dec 2017 20:26
ISWC 2017 SLIDES – Supporting Springer Nature Editors by means of Semantic Technologies
Supporting Springer Nature Editors by means of Semantic Technologies from Francesco...
Slides
23 Oct 2017 14:22
EKAW 2016 SLIDES – TechMiner: Extracting Technologies from Academic Publications
EKAW 2016 - TechMiner: Extracting Technologies from Academic Publications from Francesco...
Slides
23 Nov 2016 23:35
Publications
2026
Salatino, Angelo; Osborne, Francesco; Recupero, Diego Reforgiato; Angioni, Simone and Motta, Enrico (2026). Does Diversity of Expertise Drive Citation Impact? Evidence from Computer Science. Scientometrics, 131 pp. 1119–1146.
Does Diversity of Expertise Drive Citation Impact? Evidence from Computer Science
Aggarwal, Tanay; Salatino, Angelo; Osborne, Francesco and Motta, Enrico (2026). Large language models for scholarly ontology generation: An extensive analysis in the engineering field. Information Processing & Management, 63(1),
Large language models for scholarly ontology generation: An extensive analysis in the engineering field
2025
Murgia, Marco; Dessi, Danilo; Osborne, Francesco; Buscaldi, Davide; Motta, Enrico and Recupero, Diego Reforgiato (2025). CiteGen: A Web Application for Citation Recommendation Powered by LLMs and Knowledge Graphs. In: The Semantic Web: ESWC 2025 Satellite Events, 01-05 Jun 2025, Portoroz, Slovenia.
CiteGen: A Web Application for Citation Recommendation Powered by LLMs and Knowledge Graphs
Cadeddu, Andrea; Chessa, Alessandro; De Leo, Vincenzo; Fenu, Gianni; Motta, Enrico; Osborne, Francesco; Reforgiato Recupero, Diego; Salatino, Angelo and Secchi, Luca (2025). A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals. IEEE Access, 13 pp. 175271–175291.
A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals
Meloni, Antonello; Reforgiato Recupero, Diego; Osborne, Francesco; Salatino, Angelo Antonio; Motta, Enrico; Vahadati, Sahar and Lehmann, Jens (2025). Exploring Large Language Models for Scientific Question Answering via Natural Language to SPARQL Translation. ACM Transactions on Intelligent Systems and Technology (Early access).
Exploring Large Language Models for Scientific Question Answering via Natural Language to SPARQL Translation
Cadeddu, Andrea; Chessa, Alessandro; De Leo, Vincenzo; Fenu, Gianni; Motta, Enrico; Osborne, Francesco; Recupero, Diego Reforgiato; Salatino, Angelo and Secchi, Luca (2025). Benchmarking Large Language Models for Sustainable Development Goals Classification: Evaluating In-Context Learning and Fine-Tuning Strategies. In: 3rd International Workshop on Semantic Technologies and Deep Learning Models for Scientific, Technical and Legal Data (SemTech4STLD 2025), 01 Jun 2025, Portoroz, Slovenia.
Benchmarking Large Language Models for Sustainable Development Goals Classification: Evaluating In-Context Learning and Fine-Tuning Strategies
Motta, Enrico; Daga, Enrico; Gangemi, Aldo; Gjelsvik, Maia Lunde; Osborne, Francesco and Salatino, Angelo (2025). The Epistemology of Fine-Grained News Classification. Semantic Web, 16(3),
The Epistemology of Fine-Grained News Classification
Dessí, Danilo; Osborne, Francesco; Buscaldi, Davide; Reforgiato Recupero, Diego and Motta, Enrico (2025). CS-KG 2.0: A Large-scale Knowledge Graph of Computer Science. Scientific Data, 12(1),
CS-KG 2.0: A Large-scale Knowledge Graph of Computer Science
Presutti, Valentina; Motta, Enrico and Sabou, Marta (2025). Opportunities for Knowledge Graphs in the AI landscape - An application-centric perspective. Journal of Web Semantics (Early access).
Opportunities for Knowledge Graphs in the AI landscape - An application-centric perspective
Meloni, Antonello; Recupero, Diego Reforgiato; Osborne, Francesco; Salatino, Angelo; Motta, Enrico; Vahadati, Sahar and Lehmann, Jens (2025). Assessing Large Language Models for SPARQL Query Generation in Scientific Question Answering. In: ISWC 2024 Special Session on Harmonising Generative AI and Semantic Web Technologies,, 13 Nov 2024, Baltimore, Maryland, USA.
Assessing Large Language Models for SPARQL Query Generation in Scientific Question Answering
Salatino, Angelo; Aggarwal, Tanay; Mannocci, Andrea; Osborne, Francesco and Motta, Enrico (2025). A survey of knowledge organization systems of research fields: Resources and challenges. Quantitative Science Studies, 6 pp. 567–610.
A survey of knowledge organization systems of research fields: Resources and challenges
Borrego, Agustín; Dessì, Danilo; Ayala, Daniel; Hernández, Inma; Osborne, Francesco; Recupero, Diego Reforgiato; Buscaldi, Davide; Ruiz, David and Motta, Enrico (2025). Research hypothesis generation over scientific knowledge graphs. Knowledge-Based Systems, 315
Research hypothesis generation over scientific knowledge graphs
Bongini, Paola; Rossolini, Monica; Maurino, Andrea and Osborne, Francesco (2025). The information power of social media for investment decisions: an AI-driven analysis of Reddit posts. Journal of Financial Management, Markets and Institutions, 13(02),
The information power of social media for investment decisions: an AI-driven analysis of Reddit posts
Birti, Mattia; Maurino, Andrea and Osborne, Francesco (2025). Optimizing Large Language Models for ESG Activity Detection in Financial Texts. In: ICAIF ’25: 6th ACM International Conference on AI in Finance, 15-18 Nov 2025, Singapore, Singapore.
Optimizing Large Language Models for ESG Activity Detection in Financial Texts
Buscaldi, Davide; Dessì, Danilo; Osborne, Francesco; Piras, Davide and Recupero, Diego Reforgiato (2025). Evaluating LLMs for Named Entity Recognition in Scientific Domain with Fine-Tuning and Few-Shot Learning. In: 3rd International Workshop on Semantic Technologies and Deep Learning Models for Scientific, Technical and Legal Data (SemTech4STLD 2025), 01 Jun 2025, Portoroz, Slovenia.
Evaluating LLMs for Named Entity Recognition in Scientific Domain with Fine-Tuning and Few-Shot Learning
Tsaneva, Stefani; Dessì, Danilo; Osborne, Francesco and Sabou, Marta (2025). Knowledge graph validation by integrating LLMs and human-in-the-loop. Information Processing & Management, 62(5),
Knowledge graph validation by integrating LLMs and human-in-the-loop
Greco, David; Osborne, Francesco; Pusceddu, Simone and Reforgiato Recupero, Diego (2025). Modelling big data platforms as knowledge graphs: the data platform shaper. Journal of Big Data, 12(1),
Modelling big data platforms as knowledge graphs: the data platform shaper
Fernandez, Miriam; Morales Tirado, Alba Catalina; Pavon-Perez, Angel; Duddin, Keely; Zhang, Min; Bakina, Ksenia; Bandara, Arosha; Capdevila, Rose; Lazard, Lisa and Jurasz, Olga (2025). Co-creating an Ontology of Online Gender-Based Harms: An Interdisciplinary Perspective. In: ISWC 2025 - The 24th International Semantic Web Conference, 02-06 Nov 2025, Nara, Japan.
Co-creating an Ontology of Online Gender-Based Harms: An Interdisciplinary Perspective
Allocca, Carlo; Antonini, Alessio; Pala, Riccardo; Salatino, Angelo; Naja, Iman; Ail, Rohit; Haleem, Muhammad Salman; Lopez-Perez, Laura; Gaeta, Eugenio; Pecchia, Leandro and Fico, Giuseppe (2025). Knowledge Graph Construction for Health, Lifestyle and Fitness Applications. In: Curry, Edward; Acosta, Maribel; Poveda-Villalón, Maria; van Erp, Marieke; Ojo, Adegboyega; Hose, Katja; Shimizu, Cogan and Lisena, Pasquale eds. The Semantic Web: 22nd European Semantic Web Conference, ESWC 2025, Portoroz, Slovenia, June 1–5, 2025, Proceedings, Part II. Lecture Notes in Computer Science (LNCS), 15719. Cham, CH: Springer, pp. 102–122.
Knowledge Graph Construction for Health, Lifestyle and Fitness Applications
2024
Innominato, Pasquale; Macdonald, Jamie; Saxton, Wendy; Longshaw, Laura; Granger, Rachel; Naja, Iman; Allocca, Carlo; Edwards, Ruth; Rasheed, Solah; Folkvord, Frans; de Batle, Jordi; Ail, Rohit; Motta, Enrico; Bale, Catherine; Fuller, Claire; Mullard, Anna; Subbe, Christian; Griffiths, Dawn; Wreglesworth, Nicholas; Pecchia, Leandro; Fico, Giuseppe and Antonini, Alessio (2024). Digital remote monitoring using a mobile health solution in cancer survivors: an observational pilot trial protocol. JMIR Research Protocols, 12
Digital remote monitoring using a mobile health solution in cancer survivors: an observational pilot trial protocol
Aggarwal, Tanay; Salatino, Angelo; Osborne, Francesco and Motta, Enrico (2024). Identifying Semantic Relationships Between Research Topics Using Large Language Models in a Zero-Shot Learning Setting. In: 4th International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment, Sci-K 2024, 12 Nov 2024, Baltimore.
Identifying Semantic Relationships Between Research Topics Using Large Language Models in a Zero-Shot Learning Setting
Motta, Enrico; Osborne, Francesco; Pulici, Martino M. L.; Salatino, Angelo and Naja, Iman (2024). Capturing the Viewpoint Dynamics in the News Domain. In: Proceedings of the 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW-24), 26-28 Nov 2024, Amsterdam, Netherlands.
Capturing the Viewpoint Dynamics in the News Domain
Pisu, Alessia; Pompianu, Livio; Salatino, Angelo; Osborne, Francesco; Riboni, Daniele; Motta, Enrico and Reforgiato Recupero, Diego (2024). Classifying Scientific Topic Relationships with SciBERT. In: Joint Proc. of Posters, Demos, Workshops, and Tutorials of the 20th Int.l Conf. on Semantic Systems (SEMANTiCS 2024), 17-19 Sep 2024, Amsterdam.
Classifying Scientific Topic Relationships with SciBERT
Pisu, Alessia; Pompianu, Livio; Salatino, Angelo; Osborne, Francesco; Riboni, Daniele; Motta, Enrico and Recupero, Diego Reforgiato (2024). Leveraging Language Models for Generating Ontologies of Research Topics. In: Text2KG 2024: International Workshop on Knowledge Graph Generation from Text, 28 May 2024, Hersonissos, Crete, Greece.
Leveraging Language Models for Generating Ontologies of Research Topics
Beetz, Michael; Cimiano, Philipp; Kümpel, Michaela; Motta, Enrico; Tiddi, Ilaria and Töberg, Jan-Philipp (2024). Transforming Web Knowledge into Actionable Knowledge Graphs for Robot Manipulation Tasks. In: ESWC 2024 Workshops and Tutorials Joint Proceedings, 26-27 May 2024, Heraklion, Greece.
Transforming Web Knowledge into Actionable Knowledge Graphs for Robot Manipulation Tasks
Bolanos Burgos, Francisco; Salatino, Angelo; Osborne, Francesco and Motta, Enrico (2024). Artificial intelligence for literature reviews: opportunities and challenges. Artificial Intelligence Review, 57(9),
Artificial intelligence for literature reviews: opportunities and challenges
Cadeddu, Andrea; Chessa, Alessandro; De Leo, Vincenzo; Fenu, Gianni; Motta, Enrico; Osborne, Francesco; Recupero, Diego Reforgiato; Salatino, Angelo and Secchi, Luca (2024). Optimizing Tourism Accommodation Offers by Integrating Language Models and Knowledge Graph Technologies. Information, 15(7),
Optimizing Tourism Accommodation Offers by Integrating Language Models and Knowledge Graph Technologies
Lehmann, Jens; Meloni, Antonello; Motta, Enrico; Osborne, Francesco; Recupero, Diego Reforgiato; Salatino, Angelo Antonio and Vahdati, Sahar (2024). Large Language Models for Scientific Question Answering: An Extensive Analysis of the SciQA Benchmark. In: ESWC 2024, 26-30 May 2024, Hersonissos, Greece.
Large Language Models for Scientific Question Answering: An Extensive Analysis of the SciQA Benchmark
Buscaldi, D.; Dessi, D.; Motta, E.; Murgia, M.; Osborne, F. and Recupero, D. R. (2024). Automating Citation Placement with Natural Language Processing and Transformers. In: 2nd International Workshop on Semantic Technologies and Deep Learning Models for Scientific, Technical and Legal Data, SemTech4STLD 2024, 26 May 2024, Hersonissos; Greece.
Automating Citation Placement with Natural Language Processing and Transformers
Innominato, Pasquale F; Macdonald, Jamie H; Saxton, Wendy; Longshaw, Laura; Granger, Rachel; Naja, Iman; Alloca, Carlo; Edwards, Ruth; Rasheed, Solah; Folkvord, Frans; de Batlle, Jordi; Ail, Rohit; Motta, Enrico; Bale, Catherine; Fuller, Claire; Mullard, Anna P; Subbe, Christian P; Griffiths, Dawn; Wreglesworth, Nicholas I; Pecchia, Leandro; Fico, Giuseppe and Antonini, Alessio (2024). Digital Remote Monitoring Using an mHealth Solution for Survivors of Cancer: Protocol for a Pilot Observational Study. JMIR Research Protocols, 13
Digital Remote Monitoring Using an mHealth Solution for Survivors of Cancer: Protocol for a Pilot Observational Study
Cadeddu, Andrea; Chessa, Alessandro; De Leo, Vincenzo; Fenu, Gianni; Motta, Enrico; Osborne, Francesco; Reforgiato Recupero, Diego; Salatino, Angelo and Secchi, Luca (2024). A comparative analysis of knowledge injection strategies for large language models in the scholarly domain. Engineering Applications of Artificial Intelligence, 133
A comparative analysis of knowledge injection strategies for large language models in the scholarly domain
Diakopoulos, N.; Trattner, C.; Jannach, D.; Meijer, I. Costera and Motta, E. (2024). Leveraging Professional Ethics for Responsible AI. Communications of the ACM, 67(2), pp. 19–21.
Leveraging Professional Ethics for Responsible AI
Tsaneva, Stefani; Dessì, Danilo; Osborne, Francesco and Sabou, Marta (2024). Enhancing Scientific Knowledge Graph Generation Pipelines with LLMs and Human-in-the-Loop. In: 4th International Workshop on Scientific Knowledge: Representation, Discovery, and Assessment, Sci-K 2024, 12 Nov 2024, Baltimore.
Enhancing Scientific Knowledge Graph Generation Pipelines with LLMs and Human-in-the-Loop
Zavarella, Vanni; Recupero, Diego Reforgiato; Consoli, Sergio; Fenu, Gianni; Angioni, Simone; Buscaldi, Davide; Dessí, Danilo and Osborne, Francesco (2024). Knowledge Graphs for Digital Transformation Monitoring in Social Media. In: 3rd International Workshop on Knowledge Graph Generation from Text (TEXT2KG), 26-30 May 2024, Hersonissos, Greece.
Knowledge Graphs for Digital Transformation Monitoring in Social Media
Alam, Mehwish; Buscaldi, Davide; Cochez, Michael; Gesese, Genet Asefa; Osborne, Francesco and Reforgiato Recupero, Diego (2024). Workshop on Deep Learning and Large Language Models for Knowledge Graphs (DL4KG). In: KDD '24: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 25-29 Aug 2024, Barcelona, Spain.
Workshop on Deep Learning and Large Language Models for Knowledge Graphs (DL4KG)
Zavarella, Vanni; Consoli, Sergio; Reforgiato Recupero, Diego; Fenu, Gianni; Angioni, Simone; Buscaldi, Davide; Dessí, Danilo and Osborne, Francesco (2024). Triplétoile: Extraction of knowledge from microblogging text. Heliyon, 10(12),
Triplétoile: Extraction of knowledge from microblogging text
Angioni, Simone; Consoli, Sergio; Dessì, Danilo; Osborne, Francesco; Reforgiato Recupero, Diego and Salatino, Angelo (2024). Investigating Environmental, Social, and Governance (ESG) Discussions in News: A Knowledge Graph Analysis Empowered by AI. In: 2nd International Workshop on Semantic Technologies and Deep Learning Models for Scientific, Technical and Legal Data, SemTech4STLD 2024, 26 May 2024, Hersonissos.
Investigating Environmental, Social, and Governance (ESG) Discussions in News: A Knowledge Graph Analysis Empowered by AI
Angioni, Simone; Consoli, Sergio; Dessì, Danilo; Osborne, Francesco; Reforgiato Recupero, Diego and Salatino, Angelo (2024). Exploring Environmental, Social, and Governance (ESG) Discourse in News: An AI-Powered Investigation Through Knowledge Graph Analysis. IEEE Access, 12 pp. 77269–77283.
Exploring Environmental, Social, and Governance (ESG) Discourse in News: An AI-Powered Investigation Through Knowledge Graph Analysis
Balloccu, Simone; Podda, Alessandro Sebastian; Pompianu, Livio; Saia, Roberto and Salatino, Angelo Antonio (2024). HUMAD 2024: International Workshop on Human-Centered Modeling and Adaptation for Digital Transformation. In: UMAP '24: 32nd ACM Conference on User Modeling, Adaptation and Personalization, 1-4 Jul 2024, Cagliari, Italy.
HUMAD 2024: International Workshop on Human-Centered Modeling and Adaptation for Digital Transformation
View All Publications
Awards
Best Paper Award at EKAW 2024 for groundbreaking work on capturing the political discourse in the news
A paper authored by KMi researchers Enrico Motta, Francesco Osborne, Angelo Salatino, and Iman Naja, and Martino Pulici from the Bosch Centre for Artificial Intelligence, has received the prestigious Best Research Paper Award at the 24th International Conference on Knowledge Engineering and Knowledge Management (EKAW 24).  The EKAW series of conferences provides the premier European forum...
Awards
03 Dec 2024 19:19
AIDA Dashboard team wins Best In-use Paper Award at ISWC 2022
Members of KMi’s Scholarly Knowledge Modelling Research Group have been announced as winners of the In-Use Paper Award at the International Semantic Web Conference, which is the premiere scientific venue for the Semantic Web and Knowledge Graphs community. The award was given for the paper entitled Leveraging Knowledge Graph Technologies to Assess Journals and Conferences at Springer...
Awards
31 Oct 2022 09:10
ISWC2020 – Best Demo of the Day Award
Last November, at the 19th International Semantic Web Conference, we presented one of our latest research efforts: the AIDA Dashboard. The AIDA Dashboard, is a tool that we developed in collaboration with the University of Cagliari (IT), and by integrating statistical analysis, semantic technologies, and visual analytics techniques allows users to explore and make sense of scientific...
Awards
24 Dec 2020 15:16
Finalists at DataIQ 2020 Awards
The Smart Topic Miner, which is an innovative state-of-the-art AI application for automating editorial processes at Springer Nature and improving access to scientific knowledge, has been shortlisted for the "Most Innovative use of AI" DataIQ 2020 Awards. Smart Topic Miner analyses scientific publications in Computer Science and classifies them with very high accuracy in terms of a catalogue of...
Awards
02 Oct 2020 14:20
Runner-Up at Springer Nature Hack Day in Berlin
On 26-27 April 2018, Angelo and Francesco attended the third edition of the Springer Nature Hack Day, which was held in its headquarter in Berlin. The Springer Nature Hack Day is an event that allows researchers, developers, tech companies, and Springer Nature itself, to gather together and tackle current research issues. Offering also opportunities for potential collaborations and...
Awards
01 Jun 2018 09:27
Runner-Up at Springer Nature Hack Day in London
On the 29th November 2017, Angelo, Andrea and Thiviyan attended the second edition of SpringerNature HackDay in London (@ SpringerNature Campus). Aliaksandr Birukou, Executive Editor of Computer Science at Springer Nature and collaborator of our research team at the Knowledge Media Institute, also joined our group on the HackDay. The whole event aimed at joining together the...
Awards
03 Dec 2017 23:59
Contact
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