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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 years 8 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
ICDM
2010
IEEE
121views Data Mining» more  ICDM 2010»
13 years 5 months ago
Recommending Social Events from Mobile Phone Location Data
A city offers thousands of social events a day, and it is difficult for dwellers to make choices. The combination of mobile phones and recommender systems can change the way one de...
Daniele Quercia, Neal Lathia, Francesco Calabrese,...
IPM
2011
91views more  IPM 2011»
12 years 10 months ago
Measuring the interestingness of articles in a limited user environment
Abstract-Search engines, such as Google, assign scores to news articles based on their relevancy to a query. However, not all relevant articles for the query may be interesting to ...
Raymond K. Pon, Alfonso F. Cardenas, David Buttler...
ERCIMDL
2010
Springer
165views Education» more  ERCIMDL 2010»
13 years 8 months ago
Metadata Impact on Research Paper Similarity
While collaborative filtering and citation analysis have been well studied for research paper recommender systems, content-based approaches typically restrict themselves to straigh...
Germán Hurtado Martín, Steven Schock...
ICCBR
2005
Springer
14 years 28 days 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...