@inproceedings{252bf3359b224aa293efb9ee0771fa5f,
title = "GRE: Hybrid recommendations for NSDL collections",
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.",
keywords = "Collaborative filtering, Content based, Digital libraries, Knowledge based recommendation, Recommendation systems, Text search engine, User interface",
author = "Todd Will and Anand Srinivasan and Michael Bieber and Il Im and Vincent Oria and Wu, {Yi Fang Brook}",
year = "2009",
doi = "10.1145/1555400.1555511",
language = "English (US)",
isbn = "9781605586977",
series = "Proceedings of the ACM/IEEE Joint Conference on Digital Libraries",
pages = "457",
booktitle = "JCDL'09 - Proceedings of the 2009 ACM/IEEE Joint Conference on Digital Libraries",
note = "2009 ACM/IEEE Joint Conference on Digital Libraries, JCDL'09 ; Conference date: 15-06-2009 Through 19-06-2009",
}