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» Greedy Recommending Is Not Always Optimal
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EWMF
2003
Springer
13 years 10 months ago
Greedy Recommending Is Not Always Optimal
Abstract. Recommender systems suggest objects to users. One form recommends documents or other objects to users searching information on a web site. A recommender system can be use...
Maarten van Someren, Vera Hollink, Stephan ten Hag...
JMLR
2010
225views more  JMLR 2010»
12 years 11 months ago
Hartigan's Method: k-means Clustering without Voronoi
Hartigan's method for k-means clustering is the following greedy heuristic: select a point, and optimally reassign it. This paper develops two other formulations of the heuri...
Matus Telgarsky, Andrea Vattani
GECCO
2006
Springer
163views Optimization» more  GECCO 2006»
13 years 8 months ago
The quadratic multiple knapsack problem and three heuristic approaches to it
The quadratic multiple knapsack problem extends the quadratic knapsack problem with K knapsacks, each with its own capacity Ck. A greedy heuristic fills the knapsacks one at a tim...
Amanda Hiley, Bryant A. Julstrom
LWA
2007
13 years 6 months ago
Towards Learning User-Adaptive State Models in a Conversational Recommender System
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
Tariq Mahmood, Francesco Ricci
ACMICEC
2008
ACM
272views ECommerce» more  ACMICEC 2008»
13 years 6 months ago
Adapting the interaction state model in conversational recommender systems
Conventional conversational recommender systems support interaction strategies that are hard-coded into the system in advance. In this context, Reinforcement Learning techniques h...
Tariq Mahmood, Francesco Ricci