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KDD
2009
ACM
207views Data Mining» more  KDD 2009»
16 years 5 months ago
DynaMMo: mining and summarization of coevolving sequences with missing values
Given multiple time sequences with missing values, we propose DynaMMo which summarizes, compresses, and finds latent variables. The idea is to discover hidden variables and learn ...
Lei Li, James McCann, Nancy S. Pollard, Christos F...
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
16 years 5 months ago
GraphScope: parameter-free mining of large time-evolving graphs
How can we find communities in dynamic networks of social interactions, such as who calls whom, who emails whom, or who sells to whom? How can we spot discontinuity timepoints in ...
Jimeng Sun, Christos Faloutsos, Spiros Papadimitri...
STOC
2001
ACM
122views Algorithms» more  STOC 2001»
16 years 5 months ago
One-dimensional quantum walks
In this paper we analyze the behavior of quantum random walks. In particular we present several new results for the absorption probabilities in systems with both one and two absor...
Andris Ambainis, Eric Bach, Ashwin Nayak, Ashvin V...
VLDB
2007
ACM
191views Database» more  VLDB 2007»
16 years 5 months ago
Multidimensional reverse k NN search
Given a multidimensional point q, a reverse k nearest neighbor (RkNN) query retrieves all the data points that have q as one of their k nearest neighbors. Existing methods for proc...
Yufei Tao, Dimitris Papadias, Xiang Lian, Xiaokui ...
MOBIHOC
2006
ACM
16 years 4 months ago
Data storage placement in sensor networks
Data storage has become an important issue in sensor networks as a large amount of collected data need to be archived for future information retrieval. This paper introduces stora...
Bo Sheng, Qun Li, Weizhen Mao
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