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WSDM
2009
ACM
176views Data Mining» more  WSDM 2009»
14 years 3 months ago
The web changes everything: understanding the dynamics of web content
The Web is a dynamic, ever changing collection of information. This paper explores changes in Web content by analyzing a crawl of 55,000 Web pages, selected to represent different...
Eytan Adar, Jaime Teevan, Susan T. Dumais, Jonatha...
WSDM
2009
ACM
187views Data Mining» more  WSDM 2009»
14 years 3 months 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
2009
ACM
210views Data Mining» more  KDD 2009»
14 years 3 months ago
Modeling and predicting user behavior in sponsored search
Implicit user feedback, including click-through and subsequent browsing behavior, is crucial for evaluating and improving the quality of results returned by search engines. Severa...
Josh Attenberg, Sandeep Pandey, Torsten Suel
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 3 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang
ICDM
2009
IEEE
233views Data Mining» more  ICDM 2009»
14 years 3 months ago
Semi-Supervised Sequence Labeling with Self-Learned Features
—Typical information extraction (IE) systems can be seen as tasks assigning labels to words in a natural language sequence. The performance is restricted by the availability of l...
Yanjun Qi, Pavel Kuksa, Ronan Collobert, Kunihiko ...