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» An Introduction to Learning Structured Information
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91
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ICPR
2008
IEEE
16 years 5 months ago
A new objective function for sequence labeling
We propose a new loss function for discriminative learning of Markov random fields, which is an intermediate loss function between the sequential loss and the pointwise loss. We s...
Hisashi Kashima, Yuta Tsuboi
NAACL
2004
15 years 5 months ago
Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization
We consider the problem of modeling the content structure of texts within a specific domain, in terms of the topics the texts address and the order in which these topics appear. W...
Regina Barzilay, Lillian Lee
ADHOC
2008
72views more  ADHOC 2008»
15 years 4 months ago
MORA routing and capacity building in disruption-tolerant networks
Disruption-tolerant networks (DTNs) differ from other types of networks in that capacity is created by the movements of network participants. This implies that understanding and in...
Brendan Burns, Oliver Brock, Brian Neil Levine
141
Voted
ISF
2007
104views more  ISF 2007»
15 years 3 months ago
Overcoming organizational challenges to secure knowledge management
—Successful secure knowledge management requires consideration of both technical and organizational concerns. We use the example of existing industrial incident management system...
Finn Olav Sveen, Eliot Rich, Matthew Jager
CIKM
2004
Springer
15 years 9 months ago
Hierarchical document categorization with support vector machines
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
Lijuan Cai, Thomas Hofmann