A Taxonomy-Based Model for Expertise Extrapolation
While many ExpertFinder applications succeed in finding experts, their techniques are not always designed to capture the various levels at which expertise can be expressed. Indeed, expertise can be inferred from relationships between topics and subtopics in a taxonomy. The conventional wisdom is that expertise in subtopics is also indicative of expertise in higher level topics as well. The enrichment of Expertise Profiles for finding experts can therefore be facilitated by taking domain hierarchies into account. We present a novel semantics-based model for finding experts, expertise levels and collaboration levels in a peer review context, such as composing a Program Committee (PC) for a conference. The implicit coauthorship network encompassed by bibliographic data enables the possibility of discovering unknown experts within various degrees of separation in the coauthorship graph. Our results show an average of 85% recall in finding experts, when evaluated against three WWW Conference PCs and close to 80 additional comparable experts outside the immediate collaboration network of the PC Chairs.
4th International Conference on Semantic Computing, 2010.
U.S. Government work not protected by U.S. copyright.
Cameron, D. H., Aleman-Meza, B., Arpinar, I. B., Decker, S. L., & Sheth, A. P. (2010). A Taxonomy-Based Model for Expertise Extrapolation, 333-340.