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» Scalable Data Mining with Model Constraints
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AAI
2007
132views more  AAI 2007»
13 years 7 months ago
Incremental Extraction of Association Rules in Applicative Domains
In recent years, the KDD process has been advocated to be an iterative and interactive process. It is seldom the case that a user is able to answer immediately with a single query...
Arianna Gallo, Roberto Esposito, Rosa Meo, Marco B...
WSDM
2012
ACM
283views Data Mining» more  WSDM 2012»
12 years 3 months ago
The life and death of online groups: predicting group growth and longevity
We pose a fundamental question in understanding how to identify and design successful communities: What factors predict whether a community will grow and survive in the long term?...
Sanjay Ram Kairam, Dan J. Wang, Jure Leskovec
RECSYS
2010
ACM
13 years 7 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
ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
14 years 2 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...
KDD
2012
ACM
207views Data Mining» more  KDD 2012»
11 years 10 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang