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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
14 years 8 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
203views Data Mining» more  KDD 2009»
14 years 8 months ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
KDD
2009
ACM
170views Data Mining» more  KDD 2009»
14 years 8 months ago
Genre-based decomposition of email class noise
Corruption of data by class-label noise is an important practical concern impacting many classification problems. Studies of data cleaning techniques often assume a uniform label ...
Aleksander Kolcz, Gordon V. Cormack
WWW
2004
ACM
14 years 8 months ago
Learning block importance models for web pages
Some previous works show that a web page can be partitioned to multiple segments or blocks, and usually the importance of those blocks in a page is not equivalent. Also, it is pro...
Ruihua Song, Haifeng Liu, Ji-Rong Wen, Wei-Ying Ma
KDD
2005
ACM
192views Data Mining» more  KDD 2005»
14 years 8 months ago
Modeling and predicting personal information dissemination behavior
In this paper, we propose a new way to automatically model and predict human behavior of receiving and disseminating information by analyzing the contact and content of personal c...
Xiaodan Song, Ching-Yung Lin, Belle L. Tseng, Ming...