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SCIENTOMETRICS
2011

Accuracy of inter-researcher similarity measures based on topical and social clues

7 years 9 months ago
Accuracy of inter-researcher similarity measures based on topical and social clues
Scientific literature recommender systems (SLRSs) provide papers to researchers according to their scientific interests. Systems rely on inter-researcher similarity measures that are usually computed according to publication contents (i.e., by extracting paper topics and citations). We highlight two major issues related to this design. The required full-text access and processing are expensive and hardly feasible. Moreover, clues about meetings, encounters, and informal exchanges between researchers (which are related to a social dimension) were not exploited to date. In order to tackle these issues, we propose an original SLRS based on a threefold contribution. First, we argue the case for defining inter-researcher similarity measures building on publicly available metadata. Second, we define topical and social measures that we combine together to issue socio-topical recommendations. Third, we conduct an evaluation with 71 volunteer researchers to check researchers’ perception
Guillaume Cabanac
Added 17 Sep 2011
Updated 17 Sep 2011
Type Journal
Year 2011
Where SCIENTOMETRICS
Authors Guillaume Cabanac
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