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., Thanapalasingam, T., Mannocci, A., Osborne, F. and Motta, E. (2018) Classifying Research Papers with the Computer Science Ontology, Poster at International Semantic Web Conference, Posters & Demonstrations and Industry Tracks, MONTEREY, CALIFORNIA, USA ISWC 2018
Thanapalasingam, T., Osborne, F., Birukou, A. and Motta, E. (2018) Ontology-Based Recommendation of Editorial Products, The International Semantic Web Conference 2018, Monterey, California, USA
Osborne, F. and Motta, E. (2018) Pragmatic Ontology Evolution: Reconciling User Requirements and Application Performance, International Semantic Web Conference 2018, Monterey, California, USA
Salatino, A.A., Thanapalasingam, T., Mannocci, A., Osborne, F. and Motta, E. (2018) The Computer Science Ontology: A Large-Scale Taxonomy of Research Areas, The International Semantic Web Conference 2018, Monterey, California, USA
Thanapalasingam, T., Osborne, F., Birukou, A., Motta, E. and , d. (2018) The Smart Book Recommender: An Ontology-Driven Application for Recommending Editorial Products, Demo at International Semantic Web Conference 2018, Monterey, California, USA