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 page, we present the CSO Classifier, a new unsupervised approach for automatically classifying research papers according […]
The AIDA 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. Compared to other state-of-the-art solutions, it introduces three novel […]
The SKM3 team at the OU’s Knowledge Media Institute and Springer Nature have signed a new agreement, extending their collaboration in the area of scholarly analytics until January 2021. The collaboration between the SKM3 team and Springer Nature started in 2014 and has continued without interruptions for the past 5 years. This partnership focuses on […]
Smart Topic Miner Smart Topic Miner (STM) is an application that assists the Springer Nature editorial team in classifying the scientific literature in Computer Science in terms of a catalogue of about 15K research topics, with a very high degree of accuracy. This catalogue was itself generated by our team using a highly innovative knowledge […]
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 […]
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 […]
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. The traditional way to address the problem of identifying and […]
On March 22, 2024, the AI for the Research Ecosystem workshop (#AI4RE) took place in London, kindly hosted by UCL in the wonderful surroundings of Chandler House. The workshop was part of the Turing Institue’s AI UK Fringe series of events which took place around the U.K. The workshop focused on the intersection of the recent developments in Artificial Intelligence, such as Large Language...
The 22nd International Semantic Web Conference (ISWC 2023), a leading global event for the Semantic Web and Knowledge Graph Community, has successfully wrapped up, marked by notable involvement from our team. In this year’s edition, Francesco Osborne acted as Senior Research Track PC and Angelo Salatino as Research Track PC. Francesco has also co-organised the Workshop on Deep Learning for...
On 1 October 2023, Tanay Aggarwal joined our team, starting his doctoral research under the supervision of Dr Angelo Salatino, Dr Francesco Osborne, and Prof Enrico Motta. Tanay will investigate novel AI solutions for (semi)automatically generating ontologies of research topics. Tanay is not a new face to us, as he joined our team back in 2021 for two visiting periods, collaborating with...
This week STI 2023 – the 27th International Conference on Science, Technology and Innovation Indicators – took place. The Scientometrics community from all around the world gathered in Leiden, Netherlands, to discuss about improving scholarly evaluation practices in the light of cultural change. The conference was organised by CWTS (Leiden University) in collaboration with the European...
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