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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 12 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
KDD
2009
ACM
193views Data Mining» more  KDD 2009»
14 years 12 months ago
Probabilistic frequent itemset mining in uncertain databases
Probabilistic frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard "certain&quo...
Andreas Züfle, Florian Verhein, Hans-Peter Kr...
KDD
2009
ACM
229views Data Mining» more  KDD 2009»
14 years 12 months ago
An association analysis approach to biclustering
The discovery of biclusters, which denote groups of items that show coherent values across a subset of all the transactions in a data set, is an important type of analysis perform...
Gaurav Pandey, Gowtham Atluri, Michael Steinbach, ...
KDD
2009
ACM
211views Data Mining» more  KDD 2009»
14 years 12 months ago
Address standardization with latent semantic association
Address standardization is a very challenging task in data cleansing. To provide better customer relationship management and business intelligence for customer-oriented cooperates...
Honglei Guo, Huijia Zhu, Zhili Guo, Xiaoxun Zhang,...
KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 12 months ago
BBM: bayesian browsing model from petabyte-scale data
Given a quarter of petabyte click log data, how can we estimate the relevance of each URL for a given query? In this paper, we propose the Bayesian Browsing Model (BBM), a new mod...
Chao Liu 0001, Christos Faloutsos, Fan Guo
KDD
2009
ACM
223views Data Mining» more  KDD 2009»
14 years 12 months ago
Collaborative filtering with temporal dynamics
Customer preferences for products are drifting over time. Product perception and popularity are constantly changing as new selection emerges. Similarly, customer inclinations are ...
Yehuda Koren
KDD
2009
ACM
164views Data Mining» more  KDD 2009»
14 years 12 months ago
Social influence analysis in large-scale networks
In large social networks, nodes (users, entities) are influenced by others for various reasons. For example, the colleagues have strong influence on one's work, while the fri...
Jie Tang, Jimeng Sun, Chi Wang, Zi Yang
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 12 months ago
Constant-factor approximation algorithms for identifying dynamic communities
We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
Chayant Tantipathananandh, Tanya Y. Berger-Wolf
KDD
2009
ACM
152views Data Mining» more  KDD 2009»
14 years 12 months ago
A multi-relational approach to spatial classification
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...
Richard Frank, Martin Ester, Arno Knobbe