[PDF] Top 20 Word Clustering and Disambiguation Based on Co occurrence Data
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Word Clustering and Disambiguation Based on Co occurrence Data
... Figure 4: Compound noun disambiguation results We next conducted structural disambiguation on the test data, using the probabilities estimated based on 2D-Clustering and Brown.. We also [r] ... See full document
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Word Clustering and Disambiguation Based on Co occurrence Data
... Word Clustering and Disambiguation Based on Co occurrence Data W o r d C l u s t e r i n g a n d D i s a m b i g u a t i o n B a s e d o n C o o c c u r r e n c e D a t a H a n g Li and N a o k i A b[.] ... See full document
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Fine Grained Word Sense Disambiguation Based on Parallel Corpora, Word Alignment, Word Clustering and Aligned Wordnets
... sense clustering based on translation equivalents, as discussed in (Ide, et ...the clustering method after the wordnet-based method has been applied, and therefore each cluster containing an ... See full document
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A Semi Supervised Feature Clustering Algorithm with Application to Word Sense Disambiguation
... feature clustering for word sense disambiguation, and propose a semi- supervised feature clustering ...feature clustering methods ...training data (labeled data) by the ... See full document
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Chinese Word Sense Disambiguation based on Context Expansion
... WSD based on context expansion, which acquires WSD knowledge from synonymy ...ambiguous word can be substituted by synonymy, and the new context represented by synonymy expresses the same meaning, thus the ... See full document
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Iterative Constrained Clustering for Subjectivity Word Sense Disambiguation
... inventories based on ev- idence found in ...a word in cor- pora and groups them into coherent ...definition based on the common attributes of the ...a word, so that we can label each induced ... See full document
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Co training and Self training for Word Sense Disambiguation
... of word sense disambiguation consists in assign- ing the most appropriate meaning to a polysemous word within a given ...tagged occurrence of a par- ticular word is transformed into a ... See full document
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Answering List Questions using Co-occurrence and Clustering
... is based on Distributional Hypothesis, which states that words occurring in the same contexts tend to have similar meanings (Harris, ...human word usage can be used to figure out what people mean, at least ... See full document
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Perceptually Grounded Selectional Preferences
... predicate-argument co- occurrence ...performs word sense disambiguation and part-of-speech (PoS) tag- ging of Flickr tag sequences to extract verb-noun co-occurrence; (2) ... See full document
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Chinese Name Disambiguation Based on Adaptive Clustering with the Attribute Features
... fuzzy clustering is a com- mon clustering method in pattern recognition, and has achieved very good effect on pre-classification of characters in Chinese character recognition [8] and classification and ... See full document
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Meaningful Clustering of Senses Helps Boost Word Sense Disambiguation Performance
... for clustering WordNet senses, based on the Minimum Description Length, is described by Tomuro ...The clustering is evaluated against WordNet cousins and used for the study of inter-annotator ... See full document
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Pattern Based Disambiguation for Natural Language Processing
... For example, in confusable word set disambiguation, systems typically use as features the occurrence of a particular word within a window o f +/- n words o f the target, and collocations[r] ... See full document
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Semi supervised training of a Kernel PCA Based Model for Word Sense Disambiguation
... target word whose context contains a combination of features that may in fact be interdependent, but are not similar to any combinations that occurred in the limited amounts of labeled training ...sparse ... See full document
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Word Sense Disambiguation based Sentence Similarity
... of word sense disambiguation (WSD) on measuring sentence ...polysemous word within a specific context (Wang et al., 2006). Corpus-based methods typically compute sentence similarity ... See full document
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Lexical Co occurrence, Statistical Significance, and Word Association
... Lexical co-occurrence is an important cue for detecting word ...of word association based on a new notion of statistical significance for lex- ical ...expected ... See full document
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Evaluating a Semantic Network Automatically Constructed from Lexical Co occurrence on a Word Sense Disambiguation Task
... annotation data from Wikipe- dia, including sense labels, the titles of other pages linked to by any two related nouns, and the folk- sonomic categories to which articles ... See full document
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Learning of word sense disambiguation rules by Co-training, checking co-occurrence of features
... training data unless that instance has a reliable label. In Co-training, because of the conditional independence as- sumption, we only have to add an instance with a reliable label to labeled training ... See full document
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Multi-View Information-Theoretic Co-Clustering for Co-Occurrence Data
... of co-occurring matrices (rows for samples and columns for features) can be viewed as the frequency or counts of a certain feature occurred in a certain ...the co-occurrence analysis is ... See full document
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Co Occurrence Cluster Features for Lexical Substitutions in Context
... Sense Disambiguation (WSD, see (Agirre and Edmonds, 2006) for an extensive overview) is commonly seen as an enabling technology for applications like semantic parsing, semantic role labeling and semantic ... See full document
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Co-occurrence graphs for word sense disambiguation in the biomedical domain
... The co-occurrence graph used by the approach presented here is based on the hypothesis that documents are consistent, ...frequently co-occurring in the same documents are linked in the ...the ... See full document
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