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» Unsupervised Natural Language Processing Using Graph Models
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EMNLP
2010
13 years 3 months ago
Word Sense Induction Disambiguation Using Hierarchical Random Graphs
Graph-based methods have gained attention in many areas of Natural Language Processing (NLP) including Word Sense Disambiguation (WSD), text summarization, keyword extraction and ...
Ioannis P. Klapaftis, Suresh Manandhar
EMNLP
2009
13 years 3 months ago
Classifier Combination for Contextual Idiom Detection Without Labelled Data
We propose a novel unsupervised approach for distinguishing literal and non-literal use of idiomatic expressions. Our model combines an unsupervised and a supervised classifier. T...
Linlin Li, Caroline Sporleder
NIPS
2008
13 years 6 months ago
Shared Segmentation of Natural Scenes Using Dependent Pitman-Yor Processes
We develop a statistical framework for the simultaneous, unsupervised segmentation and discovery of visual object categories from image databases. Examining a large set of manuall...
Erik B. Sudderth, Michael I. Jordan
CICLING
2003
Springer
13 years 10 months ago
Sentence Co-occurrences as Small-world Graphs: A Solution to Automatic Lexical Disambiguation
This paper presents a graph-theoretical approach to lexical disambiguation on word co-occurrences. Producing a dictionary similar to WordNet, this method is the counterpart to word...
Stefan Bordag
NIPS
2001
13 years 6 months ago
Natural Language Grammar Induction Using a Constituent-Context Model
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Dan Klein, Christopher D. Manning