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» Stochastic processes and temporal data mining
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WSDM
2009
ACM
187views Data Mining» more  WSDM 2009»
14 years 24 days ago
Speeding up algorithms on compressed web graphs
A variety of lossless compression schemes have been proposed to reduce the storage requirements of web graphs. One successful approach is virtual node compression [7], in which of...
Chinmay Karande, Kumar Chellapilla, Reid Andersen
KDD
2008
ACM
164views Data Mining» more  KDD 2008»
14 years 6 months ago
Microscopic evolution of social networks
We present a detailed study of network evolution by analyzing four large online social networks with full temporal information about node and edge arrivals. For the first time at ...
Jure Leskovec, Lars Backstrom, Ravi Kumar, Andrew ...
WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
14 years 3 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
ICDM
2010
IEEE
273views Data Mining» more  ICDM 2010»
13 years 4 months ago
Learning Maximum Lag for Grouped Graphical Granger Models
Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
Amit Dhurandhar
KDD
2012
ACM
229views Data Mining» more  KDD 2012»
11 years 8 months ago
Finding trendsetters in information networks
Influential people have an important role in the process of information diffusion. However, there are several ways to be influential, for example, to be the most popular or the...
Diego Sáez-Trumper, Giovanni Comarela, Virg...