[PDF] Top 20 Maximum Entropy Models for Word Sense Disambiguation
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Maximum Entropy Models for Word Sense Disambiguation
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A Maximum Entropy based Word Sense Disambiguation System
... Coling2002MxEcr2 dvi A Maximum Entropy based Word Sense Disambiguation system? Armando Su?arez Manuel Palomar Departamento de Lenguajes y Sistemas Inform?aticos Universidad de Alicante Apartado de cor[.] ... See full document
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Neural Sequence Learning Models for Word Sense Disambiguation
... Word Sense Disambiguation models ex- ist in many ...a word expert for every disambiguation ...the disambiguation problem: we propose and study in depth a series of ... See full document
12
A Review on Word Sense Disambiguation
... statistical models of how fundamental sources could produce the input and other one is Feature extraction techniques: attempt to take out statistical regularities straightly from the ... See full document
6
Word Sense Disambiguation Incorporating Lexical and Structural Semantic Information
... stochastic models (Riezler et ...for word sense disambiguation (Steven- son, ...of sense information together with symbolic grammars and statistical ...lexicalized models comes ... See full document
9
Topic Models for Word Sense Disambiguation and Token Based Idiom Detection
... frequent sense baseline on nouns, but not on other parts- ...frequent sense baseline by including the prior sense probability, the performance on ad- jectives and adverbs remains below the most fre- ... See full document
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Sense Embeddings in Knowledge Based Word Sense Disambiguation
... different word embeddings ...best word embeddings model’s score (using Baroni et ...of word embeddings creation, ...the word embeddings models, or due to the different corpora they were ... See full document
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A word sense disambiguation corpus for Urdu
... proper sense of a word in a particular ...testing models based on features extracted using WSD ...one word from the left, and one word from right side of target ...target word ... See full document
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Determining the Difficulty of Word Sense Disambiguation
... lowest entropy of the three corpora while the opposite is true for ...the sense distributions that are found in corpora which are often highly ...possible sense. Consequently informa- tion about the ... See full document
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Domain Kernels for Word Sense Disambiguation
... Domain Models allows us to reduce the amount of training data, opening an interesting research di- rection for all those NLP tasks for which the Knowl- edge Acquisition Bottleneck is a crucial ...each word ... See full document
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A Topic Model for Word Sense Disambiguation
... While the topics presented in Table 2 resemble the topics one would obtain through models like LDA (Blei et al., 2003), they are not identical. Be- cause of the lengthy process of Gibbs sampling, we initially ... See full document
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Semi supervised Word Sense Disambiguation with Neural Models
... by averaging context vectors of all training sentences of the same sense. We observed in a few cases that the context vector is far from the held-out word’s embedding, especially when the input sentence is not ... See full document
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Learning Expressive Models for Word Sense Disambiguation
... the disambiguation models, that is, knowledge that goes beyond simple features extracted directly from the corpus, like bags-of-words and colloca- tions, or provided by shallow natural language tools like ... See full document
8
Word Sense Disambiguation Using Statistical Models of Roget’s Categories Trained on Large Corpora
... Word Sense Disambiguation Using Statistical Models of Roget's Categories Trained on Large Corpora Word Sense Disambiguation Using Statistical Models of Roget's Categories Trained on Large Corpora Davi[.] ... See full document
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A Lemma Based Approach to a Maximum Entropy Word Sense Disambiguation System for Dutch
... vised word sense disambiguation (WSD) sys- tem for Dutch which combines statistical classi- fication (maximum entropy) with linguistic in- ...ambiguous word in one classi- fier, ... See full document
7
Word Sense Disambiguation Using Decomposable Models
... In our approach to disambiguation, a contextual feature is judged to be informative i.e., correlated with the sense tag of the ambiguous word if the model for independence between that f[r] ... See full document
8
Word Sense Disambiguation with Multilingual Features
... ambiguous word by assigning it a different translation depending on the context where it ...frequent sense, namely that of construct (WordNet: make by combining materials and parts), and this sense ... See full document
10
Word sense disambiguation and information retrieval
... intended sense of each query word and that word’s sense in a number of the retrieved ...document word sense matches (or ...a sense mismatch was more likely to happen when the ... See full document
11
Error Driven Word Sense Disambiguation
... Error Driven Word Sense Disambiguation Error D r i v e n W o r d S e n s e D i s a m b i g u a t i o n L u c a D i n i a n d V i t t o r i o D i T o m a s o F r 6 d 6 r i q u e S e g o n d C E L I X e[.] ... See full document
5
Similarity based Word Sense Disambiguation
... 4 The weight of a w o r d estimates its expected contribution to the disambiguation task and is a product of several factors: the frequency of the w o r d in the corpus; its frequency in[r] ... See full document
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