Category Archives: Technology

The Computer Science Ontology (CSO)

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 […]

Technology-Topic Framework

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 – Early Forecasting of Research Trends

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 […]

Supporting editorial activities at Springer Nature

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

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 […]

Smart Book Recommender

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: Automatic generation of large scale taxonomies of research areas

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 […]

TechMiner

TechMiner is a novel approach, which combines natural language processing, machine learning and semantic technologies, for mining technologies from research publications and generating an OWL ontology describing their relationships with other research entities. The resulting knowledge base can support tasks such as: richer semantic search, richer expert search, monitoring the emergence and impact of new […]

Smart Topic Miner

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. STM was developed to support the Springer Nature Computer Science editorial team in classifying proceedings in the LNCS family. It analyses […]