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» Efficient Frequent Pattern Mining in Relational Databases
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ICCV
2009
IEEE
1331views Computer Vision» more  ICCV 2009»
14 years 10 months ago
I know what you did last summer: object-level auto-annotation of holiday snaps
The state-of-the art in visual object retrieval from large databases allows to search millions of images on the object level. Recently, complementary works have proposed systems ...
Stephan Gammeter, Lukas Bossard, Till Quack, Luc V...
SAC
2009
ACM
14 years 17 days ago
Applying latent dirichlet allocation to group discovery in large graphs
This paper introduces LDA-G, a scalable Bayesian approach to finding latent group structures in large real-world graph data. Existing Bayesian approaches for group discovery (suc...
Keith Henderson, Tina Eliassi-Rad
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 6 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
KDD
2009
ACM
248views Data Mining» more  KDD 2009»
13 years 10 months ago
PSkip: estimating relevance ranking quality from web search clickthrough data
1 In this article, we report our efforts in mining the information encoded as clickthrough data in the server logs to evaluate and monitor the relevance ranking quality of a commer...
Kuansan Wang, Toby Walker, Zijian Zheng
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 7 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar