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» Extractive summarization using a latent variable model
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ESANN
2004
13 years 9 months ago
Neural networks for data mining: constrains and open problems
When we talk about using neural networks for data mining we have in mind the original data mining scope and challenge. How did neural networks meet this challenge? Can we run neura...
Razvan Andonie, Boris Kovalerchuk
CSUR
1999
159views more  CSUR 1999»
13 years 7 months ago
Hubs, authorities, and communities
The Web can be naturally modeled as a directed graph, consisting of a set of abstract nodes (the pages) joined by directional edges (the hyperlinks). Hyperlinks encode a considerab...
Jon M. Kleinberg
CSDA
2007
169views more  CSDA 2007»
13 years 7 months ago
A null space method for over-complete blind source separation
In blind source separation, there are M sources that produce sounds independently and continuously over time. These sounds are then recorded by m receivers. The sound recorded by ...
Ray-Bing Chen, Ying Nian Wu
BIBE
2007
IEEE
169views Bioinformatics» more  BIBE 2007»
14 years 1 months ago
Combining Semantics, Context, and Statistical Evidence in Genomics Literature Search
—We present an information retrieval model for combining evidence from concept-based semantics, term statistics, and context for improving search precision of genomics literature...
Jay Urbain, Nazli Goharian, Ophir Frieder
WSDM
2009
ACM
161views Data Mining» more  WSDM 2009»
14 years 2 months ago
Predicting the readability of short web summaries
Readability is a crucial presentation attribute that web summarization algorithms consider while generating a querybaised web summary. Readability quality also forms an important ...
Tapas Kanungo, David Orr