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» Unsupervised Natural Language Processing Using Graph Models
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EMNLP
2009
13 years 8 months ago
Graph Alignment for Semi-Supervised Semantic Role Labeling
Unknown lexical items present a major obstacle to the development of broadcoverage semantic role labeling systems. We address this problem with a semisupervised learning approach ...
Hagen Fürstenau, Mirella Lapata
NLPRS
2001
Springer
14 years 3 months ago
A Bayesian Approach to Semi-Supervised Learning
Recent research in automated learning has focused on algorithms that learn from a combination of tagged and untagged data. Such algorithms can be referred to as semi-supervised in...
Rebecca F. Bruce
KDD
2009
ACM
200views Data Mining» more  KDD 2009»
14 years 5 months ago
Visual analysis of documents with semantic graphs
In this paper, we present a technique for visual analysis of documents based on the semantic representation of text in the form of a directed graph, referred to as semantic graph....
Delia Rusu, Blaz Fortuna, Dunja Mladenic, Marko Gr...
INLG
2010
Springer
13 years 8 months ago
A Discourse-Aware Graph-Based Content-Selection Framework
This paper presents an easy-to-adapt, discourse-aware framework that can be utilized as the content selection component of a generation system whose goal is to deliver descriptive...
Seniz Demir, Sandra Carberry, Kathleen F. McCoy
NAACL
2007
14 years 6 days ago
Data-Driven Graph Construction for Semi-Supervised Graph-Based Learning in NLP
Graph-based semi-supervised learning has recently emerged as a promising approach to data-sparse learning problems in natural language processing. All graph-based algorithms rely ...
Andrei Alexandrescu, Katrin Kirchhoff