rexplore technology full details
Professor of Knowledge Technologies
Timeline:01 Nov 2012
Exploring Research Data
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 new topics, the evolution of communities within a particular area, and several others.
To identify a variety of interesting relations between researchers, e.g., recognizing authors who share similar research trajectories. These relations go well beyond the standard co-authorship links or relationships informed by social networks, which are commonly found in other systems.
To perform fine-grained expert search with respect to detailed multi-dimensional parameters.
To analyse research performance at different levels of abstraction, including individual researchers, organizations, countries, and research communities identified on the basis of dynamic criteria.
An important aspect of Rexplore is that it 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, which automatically constructs a semantic network of fine-grained research areas, linked by semantic relations, such as sameAs and subAreaOf. The use of Klink ensures a fine-grained handling of research areas and affords Rexplore a very high level of precision and recall in associating topics to publications and researchers.
Rexplore offers an advanced graphical interface, comprising a variety of innovative and fine grained visualizations, which support users in exploring authors, topics, and research communities. To support effective exploration, all graphical elements can be clicked on, thus enabling a seamless and contextualized navigation.
13 Jan 2018
07 Dec 2017
15 Jun 2016
Salatino, A.A., Osborne, F. and Motta, E. (2018) AUGUR: Forecasting the Emergence of New Research Topics, Joint Conference on Digital Libraries 2018, Fort Worth, Texas
Osborne, F., Mannocci, A. and Motta, E. (2017) Forecasting the Spreading of Technologies in Research Communities, K-CAP 2017, Austin, Texas, USA
Salatino, A.A., Osborne, F. and Motta, E. (2017) How are topics born? Understanding the research dynamics preceding the emergence of new areas, PeerJ Computer Science
Osborne, F., Salatino, A.A., Birukou, A., Thanapalasingam, T. and Motta, E. (2017) Supporting Springer Nature Editors by means of Semantic Technologies, International Semantic Web Conference 2017 (Industry Track)
Osborne, F., Thanapalasingam, T., Salatino, A.A., Birukou, A. and Motta, E. (2017) Smart Book Recommender: A Semantic Recommendation Engine for Editorial Products, Poster at International Semantic Web Conference 2017