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» Randomized Algorithms and Complexity Theory
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SIGIR
2012
ACM
13 years 2 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
VIS
2009
IEEE
399views Visualization» more  VIS 2009»
16 years 28 days ago
Visual Human+Machine Learning
In this paper we describe a novel method to integrate interactive visual analysis and machine learning to support the insight generation of the user. The suggested approach combine...
Raphael Fuchs, Jürgen Waser, Meister Eduard Gr...
WWW
2008
ACM
16 years 12 days ago
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
We discover communities from social network data, and analyze the community evolution. These communities are inherent characteristics of human interaction in online social network...
Yu-Ru Lin, Yun Chi, Shenghuo Zhu, Hari Sundaram, B...
WWW
2004
ACM
16 years 12 days ago
Semantic email
This paper investigates how the vision of the Semantic Web can be carried over to the realm of email. We introduce a general notion of semantic email, in which an email message co...
Luke McDowell, Oren Etzioni, Alon Y. Halevy, Henry...
KDD
2008
ACM
239views Data Mining» more  KDD 2008»
16 years 3 days ago
Mining adaptively frequent closed unlabeled rooted trees in data streams
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
Albert Bifet, Ricard Gavaldà