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» Feature-based recommendation system
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CSCW
2006
ACM
15 years 10 months ago
Don't look stupid: avoiding pitfalls when recommending research papers
If recommenders are to help people be more productive, they need to support a wide variety of real-world information seeking tasks, such as those found when seeking research paper...
Sean M. McNee, Nishikant Kapoor, Joseph A. Konstan
KDD
2005
ACM
181views Data Mining» more  KDD 2005»
16 years 4 months ago
Evaluating similarity measures: a large-scale study in the orkut social network
Online information services have grown too large for users to navigate without the help of automated tools such as collaborative filtering, which makes recommendations to users ba...
Ellen Spertus, Mehran Sahami, Orkut Buyukkokten
JCDL
2005
ACM
95views Education» more  JCDL 2005»
15 years 9 months ago
Link prediction approach to collaborative filtering
Recommender systems can provide valuable services in a digital library environment, as demonstrated by its commercial success in book, movie, and music industries. One of the most...
Zan Huang, Xin Li, Hsinchun Chen
SIGIR
2012
ACM
13 years 6 months ago
Predicting the ratings of multimedia items for making personalized recommendations
Existing multimedia recommenders suggest a specific type of multimedia items rather than items of different types personalized for a user based on his/her preference. Assume tha...
Rani Qumsiyeh, Yiu-Kai Ng
IUI
2000
ACM
15 years 8 months ago
Virtual reviewers for collaborative exploration of movie reviews
We propose a collaborative exploration system that helps users to explore recommendations from various viewpoints. Given ratings and reviews on movies from reviewers, the system p...
Jun'ichi Tatemura