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» Unsupervised Learning from Linked Documents
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WWW
2009
ACM
14 years 8 months ago
Enhancing diversity, coverage and balance for summarization through structure learning
Document summarization plays an increasingly important role with the exponential growth of documents on the Web. Many supervised and unsupervised approaches have been proposed to ...
Liangda Li, Ke Zhou, Gui-Rong Xue, Hongyuan Zha, Y...
IADIS
2004
13 years 9 months ago
Electronic case studies: a problem-based learning approach
E-Cases is an innovative approach to management development. Traditional case studies typically describe a decision or a problem in a real-life setting. E-Cases encourage students...
Philip M. Drinkwater, Christopher P. Holland, K. N...
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
14 years 8 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
ICML
2005
IEEE
14 years 8 months ago
Learn to weight terms in information retrieval using category information
How to assign appropriate weights to terms is one of the critical issues in information retrieval. Many term weighting schemes are unsupervised. They are either based on the empir...
Rong Jin, Joyce Y. Chai, Luo Si
EMNLP
2008
13 years 9 months ago
Selecting Sentences for Answering Complex Questions
Complex questions that require inferencing and synthesizing information from multiple documents can be seen as a kind of topicoriented, informative multi-document summarization. I...
Yllias Chali, Shafiq R. Joty