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GFKL
2007
Springer
180views Data Mining» more  GFKL 2007»
14 years 1 months ago
Content-based Dimensionality Reduction for Recommender Systems
Recommender Systems are gaining widespread acceptance in e-commerce applications to confront the information overload problem. Collaborative Filtering (CF) is a successful recommen...
Panagiotis Symeonidis
ICWSM
2009
13 years 5 months ago
A Comparative Analysis of Trust-Enhanced Recommenders for Controversial Items
A particularly challenging task for recommender systems (RSs) is deciding whether to recommend an item that received a variety of high and low scores from its users. RSs that inco...
Patricia Victor, Chris Cornelis, Martine De Cock, ...
CIKM
2010
Springer
13 years 2 months ago
On bootstrapping recommender systems
Recommender systems perform much better on users for which they have more information. This gives rise to a problem of satisfying users new to a system. The problem is even more a...
Nadav Golbandi, Yehuda Koren, Ronny Lempel
SIGIR
2010
ACM
13 years 11 months ago
Temporal diversity in recommender systems
Collaborative Filtering (CF) algorithms, used to build webbased recommender systems, are often evaluated in terms of how accurately they predict user ratings. However, current eva...
Neal Lathia, Stephen Hailes, Licia Capra, Xavier A...
SENSYS
2006
ACM
14 years 1 months ago
Target tracking with binary proximity sensors: fundamental limits, minimal descriptions, and algorithms
We explore fundamental performance limits of tracking a target in a two-dimensional field of binary proximity sensors, and design algorithms that attain those limits. In particul...
Nisheeth Shrivastava, Raghuraman Mudumbai, Upamany...