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IIR
2010
15 years 8 months ago
An Empirical Comparison of Collaborative Filtering Approaches on Netflix Data
Recommender systems are widely used in E-Commerce for making automatic suggestions of new items that could meet the interest of a given user. Collaborative Filtering approaches co...
Nicola Barbieri, Massimo Guarascio, Ettore Ritacco
DMSN
2008
ACM
15 years 8 months ago
A substrate for in-network sensor data integration
With the ultimate goal of extending the data integration paradigm and query processing capabilities to ad hoc wireless networks, sensors, and stream systems, we consider how to su...
Svilen R. Mihaylov, Marie Jacob, Zachary G. Ives, ...
EMNLP
2011
14 years 6 months ago
Approximate Scalable Bounded Space Sketch for Large Data NLP
We exploit sketch techniques, especially the Count-Min sketch, a memory, and time efficient framework which approximates the frequency of a word pair in the corpus without explic...
Amit Goyal, Hal Daumé III
KDD
2009
ACM
257views Data Mining» more  KDD 2009»
16 years 1 months ago
Argo: intelligent advertising by mining a user's interest from his photo collections
In this paper, we introduce a system named Argo which provides intelligent advertising made possible from users’ photo collections. Based on the intuition that user-generated ph...
Xin-Jing Wang, Mo Yu, Lei Zhang, Rui Cai, Wei-Ying...
WISE
2010
Springer
15 years 4 months ago
Neighborhood-Restricted Mining and Weighted Application of Association Rules for Recommenders
Abstract. Association rule mining algorithms such as Apriori were originally developed to automatically detect patterns in sales transactions and were later on also successfully ap...
Fatih Gedikli, Dietmar Jannach