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» Context-Dependent Term Relations for Information Retrieval
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76
Voted
KDD
2009
ACM
152views Data Mining» more  KDD 2009»
15 years 10 months ago
TANGENT: a novel, 'Surprise me', recommendation algorithm
Most of recommender systems try to find items that are most relevant to the older choices of a given user. Here we focus on the "surprise me" query: A user may be bored ...
Kensuke Onuma, Hanghang Tong, Christos Faloutsos
KDD
2005
ACM
161views Data Mining» more  KDD 2005»
15 years 10 months ago
Combining email models for false positive reduction
Machine learning and data mining can be effectively used to model, classify and discover interesting information for a wide variety of data including email. The Email Mining Toolk...
Shlomo Hershkop, Salvatore J. Stolfo
HT
2009
ACM
15 years 4 months ago
Comparing the performance of us college football teams in the web and on the field
In previous research it has been shown that link-based web page metrics can be used to predict experts’ assessment of quality. We are interested in a related question: do expert...
Martin Klein, Olena Hunsicker, Michael L. Nelson
78
Voted
SIGMOD
2010
ACM
231views Database» more  SIGMOD 2010»
15 years 2 months ago
Automatically incorporating new sources in keyword search-based data integration
Scientific data offers some of the most interesting challenges in data integration today. Scientific fields evolve rapidly and accumulate masses of observational and experiment...
Partha Pratim Talukdar, Zachary G. Ives, Fernando ...
GECCO
2008
Springer
239views Optimization» more  GECCO 2008»
14 years 10 months ago
Multiobjective design of operators that detect points of interest in images
In this paper, a multiobjective (MO) learning approach to image feature extraction is described, where Pareto-optimal interest point (IP) detectors are synthesized using genetic p...
Leonardo Trujillo, Gustavo Olague, Evelyne Lutton,...