130,372 research outputs found
monitoraggio di impianti di depurazione della regione Campania mediante l'utilizzo di una batteria di test ecotossicologici
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Attività antibatterica e antinfiammatoria di estratti di Helicrysum litoreum Guss. (Ateraceae)
No full textPhotobacterium damsela quale possibile indicatore di intrusione di acqua marina in sorgenti termali
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Valutazione di inquinanti chimici e microbiologici aereodispersi in seguito all'uso di letame nel settore agricolo e rischio infettivo
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MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
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