Referral Web: combining social networks and collaborative filtering
Communications of the ACM
Enhancing a digital book with a reading recommender
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Searching the Web by constrained spreading activation
Information Processing and Management: an International Journal
Buckets: smart objects for digital libraries
Communications of the ACM
User Behavior Tendencies on Data Collections in a Digital Library
ECDL '02 Proceedings of the 6th European Conference on Research and Advanced Technology for Digital Libraries
Notes from the Interoperability Front: A Progress Report on the Open Archives Initiative
ECDL '02 Proceedings of the 6th European Conference on Research and Advanced Technology for Digital Libraries
The Widest Practicable Dissemination: The NASA Technical Report Server
The Widest Practicable Dissemination: The NASA Technical Report Server
World Wide Web Implementation of the Langley Technical Report Server
World Wide Web Implementation of the Langley Technical Report Server
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Latent semantic models for collaborative filtering
ACM Transactions on Information Systems (TOIS)
Distributed, real-time computation of community preferences
Proceedings of the sixteenth ACM conference on Hypertext and hypermedia
Preventing shilling attacks in online recommender systems
Proceedings of the 7th annual ACM international workshop on Web information and data management
Usage derived recommendations for a video digital library
Journal of Network and Computer Applications
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We present the user evaluation of two recommendation server methodologies implemented for the NASA Technical Report Server (NTRS). One methodology for generating recommendations uses log analysis to identify co-retrieval events on full-text documents. For comparison, we used the Vector Space Model (VSM) as the second methodology. We calculated cosine similarities and used the top 10 most similar documents (based on metadata) as "recommendations". We then ran an experiment with NASA Langley Research Center (LaRC) staff members to gather their feedback on which method produced the most "quality" recommendations. We found that in most cases VSM outperformed log analysis of co-retrievals. However, analyzing the data revealed the evaluations might have been structurally biased in favor of the VSM generated recommendations. We explore some possible methods for combining log analysis and VSM generated recommendations and suggest areas of future work.