Reviewer Profiling Using Sparse Matrix Regression

8 years 3 months ago
Reviewer Profiling Using Sparse Matrix Regression
Thousands of scientific conferences happen every year, and each involves a laborious scientific peer review process conducted by one or more busy scientists serving as Technical/Scientific Program Committee (TPC) chair(s). The chair(s) must match submitted papers to their reviewer pool in such a way that i) each paper is reviewed by experts in its subject matter; and ii) no reviewer is overloaded with reviews or under-utilized. Towards this end, seasoned TPC chairs know the value of reviewer and paper profiling: summarizing the expertise / interests of each reviewer and the subject matter of each paper using judiciously chosen domain-specific keywords. An automated profiling algorithm is proposed for this purpose, which starts from generic / noisy reviewer profiles extracted using Google Scholar and derives custom conference-centric reviewer and paper profiles. Each reviewer is expert on few sub-topics, whereas the pool of reviewers and the conference may collectively need many more ke...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos
Added 12 Feb 2011
Updated 12 Feb 2011
Type Journal
Year 2010
Where ICDM
Authors Evangelos E. Papalexakis, Nicholas D. Sidiropoulos, Minos N. Garofalakis
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