Are topic-specific search term, journal name and author name recommendations relevant for researchers?

摘要

In this paper we describe a case study where researchers in the socialsciences (n=19) assess topical relevance for controlled search terms, journalnames and author names which have been compiled automatically bybibliometric-enhanced information retrieval (IR) services. We call thesebibliometric-enhanced IR services Search Term Recommender (STR), Journal NameRecommender (JNR) and Author Name Recommender (ANR) in this paper. Theresearchers in our study (practitioners, PhD students and postdocs) were askedto assess the top n pre-processed recommendations from each recommender forspecific research topics which have been named by them in an interview beforethe experiment. Our results show clearly that the presented search term,journal name and author name recommendations are highly relevant to theresearchers' topic and can easily be integrated for search in DigitalLibraries. The average precision for top ranked recommendations is 0.75 forauthor names, 0.74 for search terms and 0.73 for journal names. The relevancedistribution differs largely across topics and researcher types. Practitionersseem to favor author name recommendations while postdocs have rated author namerecommendations the lowest. In the experiment the small postdoc group (n=3)favor journal name recommendations.