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» Improved Recommendations via (More) Collaboration
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KES
2005
Springer
13 years 10 months ago
Using Recommendation to Improve Negotiations in Agent-Based Systems
: In this paper we present research works on non-intuitive and low-efficient negotiations between agents in agent based system. We find recommendation techniques as a suitable meth...
Mateusz Lenar, Janusz Sobecki
RECSYS
2010
ACM
13 years 5 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
KDD
2005
ACM
109views Data Mining» more  KDD 2005»
14 years 5 months ago
Overcoming Incomplete User Models in Recommendation Systems Via an Ontology
Abstract. To make accurate recommendations, recommendation systems currently require more data about a customer than is usually available. We conjecture that the weaknesses are due...
Vincent Schickel-Zuber, Boi Faltings
AH
2008
Springer
13 years 11 months ago
Locally Adaptive Neighborhood Selection for Collaborative Filtering Recommendations
Abstract. User-to-user similarity is a fundamental component of Collaborative Filtering (CF) recommender systems. In user-to-user similarity the ratings assigned by two users to a ...
Linas Baltrunas, Francesco Ricci
RECSYS
2010
ACM
13 years 5 months ago
Incremental collaborative filtering via evolutionary co-clustering
Collaborative filtering is a popular approach for building recommender systems. Current collaborative filtering algorithms are accurate but also computationally expensive, and so ...
Mohammad Khoshneshin, W. Nick Street