GRE: Hybrid recommendations for NSDL collections
Document Type
Conference Proceeding
Publication Date
11-30-2009
Abstract
Recommendation systems have been proven to reduce the time and effort required by users to find relevant items, but there are only sporadic reports on their application in digital libraries. The General Recommendation Engine (GRE) is composed of the text search system Lucene augmented by the well-understood content based and collaborative filtering techniques and the first application of knowledge based recommendation in digital libraries to recommend items from 22 National Science Digital Library collections. In this study comprised of 60 subjects, the GRE statistically outperformed the baseline system Lucene in all areas of evaluation.
Identifier
70450275820 (Scopus)
ISBN
[9781605586977]
Publication Title
Proceedings of the ACM IEEE Joint Conference on Digital Libraries
External Full Text Location
https://doi.org/10.1145/1555400.1555511
ISSN
15525996
First Page
457
Recommended Citation
Will, Todd; Srinivasan, Anand; Bieber, Michael; Im, Il; Oria, Vincent; and Wu, Yi Fang Brook, "GRE: Hybrid recommendations for NSDL collections" (2009). Faculty Publications. 11828.
https://digitalcommons.njit.edu/fac_pubs/11828
