Osborne, Francesco and Motta, Enrico
(2014).
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| URL: | http://2014.eswc-conferences.org/sites/default/fil... |
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Abstract
Rexplore leverages novel solutions in data mining, semantic technologies and visual analytics, and provides an innovative environment for exploring and making sense of scholarly data. Rexplore allows users: 1) to detect and make sense of important trends in research; 2) to identify a variety of interesting relations between researchers, beyond the standard co-authorship relations provided by most other systems; 3) to perform fine-grained expert search with respect to detailed multi-dimensional parameters; 4) to detect and characterize the dynamics of interesting communities of researchers, identified on the basis of shared research interests and scientific trajectories; 5) to analyse research performance at different levels of abstraction, including individual researchers, organizations, countries, and research communities.
| Item Type: | Conference or Workshop Item |
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| Copyright Holders: | 2014 The Authors |
| Keywords: | scholarly data; visual analytics; data exploration; semantic web; ontology population; data mining; data integration |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Research Group: | Centre for Research in Computing (CRC) |
| Item ID: | 40346 |
| Depositing User: | Francesco Osborne |
| Date Deposited: | 11 Jun 2014 13:44 |
| Last Modified: | 14 Jun 2020 09:47 |
| URI: | http://oro.open.ac.uk/id/eprint/40346 |
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