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This study explores the use of citations in users' personal collections to provide personalized digital library services and examines the resolvability of citations to unique identifiers and online sources. The research aims to enhance recommender systems and understand users' research interests.
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A Study of Citations in Users’ Online Personal Collections Nishikant Kapoor John T Butler, Sean M McNee, Gary C Fouty James A Stemper, Joseph A Konstan GroupLens Research Group and University Libraries University of Minnesota, USA
Research Objectives • Design & Develop • Personalized digital library services • Understand • Users’ research interests
Research Questions Can we utilize users’ personal citation collections to offer them personalized DL services? • Can citations in users’ personal collections be resolved to unique identifiers? • How many of those do actually resolve to a unique online identifier? • How many of the resolved citations do actually lead to an online source for their content or metadata?
Citation Collections • RefWorks users • 96 collections, 30,336 citations • Two outliers (4000+ and 7000+) 316
Citation Types J B R N D S
Citation Types W J B R N D
Resolvability • A citation is resolvable if it has • A valid unique ID : DOI for articles, ISBN for books • Enough information to resolve it to a unique ID All citations that can be represented using a valid unique ID, are potentially resolvable. Unique ID of identical citations in different collections is key to building similarities between users.
External Resolvers • DOI and OpenURL Query Interfaces • Citation resolvers at crossref.org (CR) • ISBN Query Interfaces • Citation resolver at worldcat.org (WC)
Validity • A URL is valid if it leads to a citation’s source online • URLs : URL may or may not be unique • Validated existence of URL, not its accuracy • Did not attempt to retrieve ID for citation
DOI Resolvability 0 0 0 0
Resolvability Summary 8,540 (47%)
Limitations & Concerns • Very limited resolvers were used • Additional resolvers such as the Citation Matcher from PubMed could enhance resolvability further • Dataset too small and too diverse • Difficult to find correlation among users • CF based services work better with larger dataset • Privacy concerns • Users want (a) control (b) anonymity
Future Work • Survey - Users’ willingness to share their personal collections • Understand how truly do users’ personal collections represent their profile? • Prototype of CF based DL services http://techlens.cs.umn.edu/ RecSys, Minneapolis, Oct 19-20, 2007
Resources • GroupLens Research Group, Dept of CSEE University of Minnesota, USA http://www.grouplens.org/ • MovieLens Recommender System http://www.movielens.org/ • TechLens Recommender System http://techlens.cs.umn.edu/
Acknowledgements • NSF grant IIS-0534939 • RefWorks (http://www.refworks.com/)
A Study of Citations in Users’ Online Personal Collections Nishikant Kapoor Questions?