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WWW
2005
ACM
16 years 4 months ago
Adaptive page ranking with neural networks
Recent developments in the area of neural networks provided new models which are capable of processing general types of graph structures. Neural networks are well-known for their ...
Franco Scarselli, Sweah Liang Yong, Markus Hagenbu...
102
Voted
EMNLP
2007
15 years 4 months ago
Incremental Text Structuring with Online Hierarchical Ranking
Many emerging applications require documents to be repeatedly updated. Such documents include newsfeeds, webpages, and shared community resources such as Wikipedia. In this paper ...
Erdong Chen, Benjamin Snyder, Regina Barzilay
EMNLP
2007
15 years 4 months ago
Enhancing Single-Document Summarization by Combining RankNet and Third-Party Sources
We present a new approach to automatic summarization based on neural nets, called NetSum. We extract a set of features from each sentence that helps identify its importance in the...
Krysta Marie Svore, Lucy Vanderwende, Christopher ...
EMNLP
2009
15 years 1 months ago
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The res...
Jianfeng Gao, Qiang Wu, Chris Burges, Krysta Marie...
134
Voted
ICONIP
2008
15 years 4 months ago
A Vector Quantization Approach for Life-Long Learning of Categories
We present a category learning vector quantization (cLVQ) approach for incremental and life-long learning of multiple visual categories where we focus on approaching the stability-...
Stephan Kirstein, Heiko Wersing, Horst-Michael Gro...