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» Mining data streams: a review
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ICWSM
2009
13 years 6 months ago
From Generating to Mining: Automatically Scripting Conversations Using Existing Online Sources
Hearing people argue opposing sides of an issue can be a useful way to understand the topic; however, these debates or conversations often don't exist. Unfortunately, generat...
Nathan D. Nichols, Lisa M. Gandy, Kristian J. Hamm...
KDD
1998
ACM
112views Data Mining» more  KDD 1998»
14 years 1 months ago
Evaluating Usefulness for Dynamic Classification
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 9 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
GFKL
2005
Springer
101views Data Mining» more  GFKL 2005»
14 years 2 months ago
Discovering Communities in Linked Data by Multi-view Clustering
Abstract. We consider the problem of finding communities in large linked networks such as web structures or citation networks. We review similarity measures for linked objects and...
Isabel Drost, Steffen Bickel, Tobias Scheffer
SADM
2011
13 years 3 months ago
Random survival forests for high-dimensional data
: Minimal depth is a dimensionless order statistic that measures the predictiveness of a variable in a survival tree. It can be used to select variables in high-dimensional problem...
Hemant Ishwaran, Udaya B. Kogalur, Xi Chen, Andy J...