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KAIS
2011
102views more  KAIS 2011»
13 years 9 days ago
Symbolic data analysis tools for recommendation systems
Recommendation Systems have become an important tool to cope with the information overload problem by acquiring data about the user behavior. After tracing the user behavior, throu...
Byron Leite Dantas Bezerra, Francisco de Assis Ten...
ICCBR
2005
Springer
13 years 11 months ago
Re-using Implicit Knowledge in Short-Term Information Profiles for Context-Sensitive Tasks
Typically, case-based recommender systems recommend single items to the on-line customer. In this paper we introduce the idea of recommending a user-defined collection of items whe...
Conor Hayes, Paolo Avesani, Emiliano Baldo, Padrai...
SIGIR
2009
ACM
13 years 12 months ago
Temporal collaborative filtering with adaptive neighbourhoods
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
Neal Lathia, Stephen Hailes, Licia Capra
AAAI
2004
13 years 6 months ago
Making Better Recommendations with Online Profiling Agents
In recent years, we have witnessed the success of autonomous agents applying machine learning techniques across a wide range of applications. However, agents applying the same mac...
Danny Oh, Chew Lim Tan
ESWA
2002
134views more  ESWA 2002»
13 years 5 months ago
A personalized recommender system based on web usage mining and decision tree induction
A personalized product recommendation is an enabling mechanism to overcome information overload occurred when shopping in an Internet marketplace. Collaborative filtering has been...
Yoon Ho Cho, Jae Kyeong Kim, Soung Hie Kim