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SIGIR
2008
ACM
13 years 7 months ago
Hierarchical naive bayes models for representing user profiles
In this paper, we show how a user profile can be enhanced when a more detailed description of the products is included. Two main assumptions have been considered: the first implie...
Juan F. Huete, Luis M. de Campos, Juan M. Fern&aac...
WEBDB
2009
Springer
159views Database» more  WEBDB 2009»
14 years 2 months ago
Beyond the Stars: Improving Rating Predictions using Review Text Content
Online reviews are an important asset for users deciding to buy a product, see a movie, or go to a restaurant, as well as for businesses tracking user feedback. However, most revi...
Gayatree Ganu, Noemie Elhadad, Amélie Maria...
WWW
2008
ACM
14 years 8 months ago
Trust-based recommendation systems: an axiomatic approach
High-quality, personalized recommendations are a key feature in many online systems. Since these systems often have explicit knowledge of social network structures, the recommenda...
Reid Andersen, Christian Borgs, Jennifer T. Chayes...
KCAP
2003
ACM
14 years 24 days ago
Capturing interest through inference and visualization: ontological user profiling in recommender systems
Tools for filtering the World Wide Web exist, but they are hampered by the difficulty of capturing user preferences in such a diverse and dynamic environment. Recommender systems ...
Stuart E. Middleton, Nigel R. Shadbolt, David De R...
RECSYS
2010
ACM
13 years 7 months ago
Collaborative filtering via euclidean embedding
Recommendation systems suggest items based on user preferences. Collaborative filtering is a popular approach in which recommending is based on the rating history of the system. O...
Mohammad Khoshneshin, W. Nick Street