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» Learning author-topic models from text corpora
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AIL
2006
130views more  AIL 2006»
13 years 9 months ago
Extractive summarisation of legal texts
We describe research carried out as part of a text summarisation project for the legal domain for which we use a new XML corpus of judgments of the UK House of Lords. These judgmen...
Ben Hachey, Claire Grover
KDD
2007
ACM
167views Data Mining» more  KDD 2007»
14 years 9 months ago
Generalized component analysis for text with heterogeneous attributes
We present a class of richly structured, undirected hidden variable models suitable for simultaneously modeling text along with other attributes encoded in different modalities. O...
Xuerui Wang, Chris Pal, Andrew McCallum
AAAI
2000
13 years 10 months ago
Information Extraction with HMM Structures Learned by Stochastic Optimization
Recent research has demonstrated the strong performance of hidden Markov models applied to information extraction--the task of populating database slots with corresponding phrases...
Dayne Freitag, Andrew McCallum
SIGIR
2002
ACM
13 years 8 months ago
A new family of online algorithms for category ranking
We describe a new family of topic-ranking algorithms for multi-labeled documents. The motivation for the algorithms stems from recent advances in online learning algorithms. The a...
Koby Crammer, Yoram Singer
ISOLA
2010
Springer
13 years 7 months ago
LivingKnowledge: Kernel Methods for Relational Learning and Semantic Modeling
Latest results of statistical learning theory have provided techniques such us pattern analysis and relational learning, which help in modeling system behavior, e.g. the semantics ...
Alessandro Moschitti