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Using a domain taxonomy for the analysis of structure and level of research: A multifaceted project in semantic data analysis

Main informationBy: Boris Mirkin (Higher School of Economics, Russian Federation)

Date: Thursday, 26th of March 2015, 16h00

Location: FCT/UNL, Seminar Room (Ed. II)
AbstractIt appears much of my efforts in the past decade went into this project even if unconsciously. I am going to present results in three of its facets: (a) analysis of the structure of research by a research organization using a taxonomy of the domain and optimal lifting to higher ranks of the taxonomy (this has been inspired by L. Moniz Pereira and further advanced by a funded project led by S. Nascimento in CENTRIA (2007-11); (b) measuring the level of research results, arguably for the first time internationally, and combining that with multiple other criteria of research impact (citation and merit), so that on our sample Hirsch index vanishes by itself; (c) defining and using a string-to-text relevance measure to get a reliable tool for automating data collection in both of the facets (a) and (b), with an experimental comparison of three different approaches.
Short-bioBoris Mirkin is a Professor at the Faculty of Computer Science, National Research University Higher School of Economics, Moscow RF. He holds a PhD in Computer Science and DSc in Systems Analysis degrees from Russian Universities. In 1991-2010 he extensively travelled taking visiting research appointments in France (1991-3), USA (1993-8), Germany (1996-9) and a teaching appointment at Birkbeck University of London, UK (2000-2010).
He develops methods for clustering and interpretation of complex data within the “data recovery” perspective. Currently these approaches are being extended to automation of text analysis problems including the development and use of hierarchical ontologies. His latest publications: textbook "Core concepts in data analysis" (Springer 2011) and monograph "Clustering: A data recovery approach" (Chapman and Hall/CRC Press, 2012).

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