The Computer Science Ontology (CSO) is a large-scale ontology of research areas that was automatically generated using the Klink-2 algorithm [1] on the Rexplore dataset [2], which consists of about 16 million publications, mainly in the field of Computer Science. The Klink-2 algorithm combines semantic technologies, machine learning, and knowledge from external sources to automatically […]
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. TTF characterizes technologies in terms of a set of topics drawn from a large-scale ontology of research areas over a given time period and applies machine learning on these data to forecast […]
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. Augur operates in three steps. First, it creates evolutionary networks describing the collaboration between research topics over […]
Couple of months ago, the SKM3 attended the Springer Nature HackDay (here is the post). Just not long ago, Springer Nature released a short video featuring us. Summarised is also Angelo’s interview, in which he discusses the advantages of making scholarly datasets, as SciGraph, available to the public.
After the great success of the past three editions, we are pleased to announce the SAVE-SD 2018 workshop. SAVE-SD aims to bring together publishers, companies and researchers from different fields (including Document and Knowledge Engineering, Semantic Web, Natural Language Processing, Scholarly Communication, Bibliometrics, Human-Computer Interaction, Information Visualisation, Bioinformatics, and Life Sciences) in order to bridge the […]
The Open University team and Springer Nature have launched a new research project with the aim of developing new innovative solutions to support editorial activities at Springer Nature. The project will be lead by Enrico Motta and Francesco Osborne and will start on May 2018. The SKM3 team and Springer Nature have been collaborating since 2015 […]
Rexplore 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. In particular, Rexplore allows users: To detect and make sense of important trends in research, such as, significant migrations of researchers from one area to another, the emergence of […]
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. It does […]
Great news for our team! A paper authored by Angelo A. Salatino, Francesco Osborne and Enrico Motta, published last June to PeerJ Computer Science journal, was one of the top 5 most viewed in the areas of Artificial Intelligence, Data Science and Digital Libraries. The paper entitled “How are topics born? Understanding the research dynamics preceding the emergence of new areas” is a […]
Forecasting the Spreading of Technologies in Research Communities @ K-CAP 2017 from Francesco Osborne
Scholarly Knowledge Mining
Digital Humanities
Data Science
Smart Cities and Robotics
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