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» Modeling Preferences in a Distributed Recommender System
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UM
2007
Springer
14 years 1 months ago
Feature-Weighted User Model 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 re...
Panagiotis Symeonidis, Alexandros Nanopoulos, Yann...
CCS
2010
ACM
13 years 10 months ago
Towards publishing recommendation data with predictive anonymization
Recommender systems are used to predict user preferences for products or services. In order to seek better prediction techniques, data owners of recommender systems such as Netfli...
Chih-Cheng Chang, Brian Thompson, Hui (Wendy) Wang...
SIGIR
2009
ACM
14 years 1 months ago
Personalized tag recommendation using graph-based ranking on multi-type interrelated objects
Social tagging is becoming increasingly popular in many Web 2.0 applications where users can annotate resources (e.g. Web pages) with arbitrary keywords (i.e. tags). A tag recomme...
Ziyu Guan, Jiajun Bu, Qiaozhu Mei, Chun Chen, Can ...
AI
2009
Springer
14 years 2 months ago
Context Dependent Movie Recommendations Using a Hierarchical Bayesian Model
Abstract. We use a hierarchical Bayesian approach to model user preferences in different contexts or settings. Unlike many previous recommenders, our approach is content-based. We...
Daniel Pomerantz, Gregory Dudek
WWW
2007
ACM
14 years 8 months ago
Modeling user behavior in recommender systems based on maximum entropy
We propose a model for user purchase behavior in online stores that provide recommendation services. We model the purchase probability given recommendations for each user based on...
Tomoharu Iwata, Kazumi Saito, Takeshi Yamada