Paper Info
Title
Investigating the potential impact of non-personalized recommendations in the OPAC: Amazon vs. WorldCat.org
Abstract
Recent research into the functionality of Online Public Access Catalogues (OPACs) has led to a call for such systems to incorporate functionality to facilitate resource discovery, and replicate the information search experience users encounter elsewhere on the Web. Recommendations represent one such feature. Developments so far in this area indicate that non-personalized or item-level recommendations are most suited to the OPAC environment. Whilst a number of such systems have been developed and implemented, research has yet to investigate fully the impact of such recommendations on user performance, search behavior, and system perceptions. This paper presents the results of an exploratory laboratory-based study comparing user behavior in Amazon, which offers non-personalized recommendations, and WorldCat.org, which does not. An analysis of task performance and participant interactions with the systems reveals that the presence of non-personalized recommendations improves resource discovery, search efficiency, and perceived usability.
Year
DOI
Venue
2014
10.1145/2637002.2637015
IIiX
Keywords
Field
DocType
design,information search behaviour,experimentation,human factors,digital libraries,recommender system,opac,measurement,recommendations,performance
Recommender system,Public access,Data mining,World Wide Web,Information retrieval,Computer science,Usability,Amazon rainforest,Replicate
Conference
Citations 
PageRank 
References 
3
0.43
25
Authors
3
Name
Order
Citations
PageRank
Simon Wakeling1418.06
Paul D. Clough231230.30
Barbara A. Sen3204.92