[PDF] Top 20 Using Three Way Data for Word Sense Discrimination
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Using Three Way Data for Word Sense Discrimination
... While it is relatively easy for a human language user to distinguish between the two senses, this is a difficult task for a computer. Even worse: the results get blurred because the attributes of both senses (in this ... See full document
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Word Sense Discrimination by Clustering Contexts in Vector and Similarity Spaces
... of using very large amounts of training data versus smaller amounts where each instance includes the tar- get word (as is the case in this ...target word. However, the data specific to ... See full document
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Linear transformations of semantic spaces for word sense discrimination and collocation compositionality grading
... these three characteristics are required for every single collocation and perhaps we should consider as a collocation any recurrent word combination that fulfils at least one of these three ...quent ... See full document
198
SemEval 2007 Task 02: Evaluating Word Sense Induction and Discrimination Systems
... Word Sense Disambiguation (WSD) is a key ...frequent sense heuristic, as attested in the all-words track of the last Sense- val competition (Snyder and Palmer, ...training data (SemCor ... See full document
6
A Sense Topic Model for Word Sense Induction with Unsupervised Data Enrichment
... Word sense induction (WSI) seeks to automat- ically discover the senses of a word in a cor- pus via unsupervised ...a sense-topic model for WSI, which treats sense and topic as two ... See full document
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Zero shot Word Sense Disambiguation using Sense Definition Embeddings
... a way to disambiguate rare and unseen words into po- tentially rare senses, supervised methods consis- tently outperform these methods in the general set- ting where inference is to be carried over both fre- ... See full document
12
Word Sense Disambiguation using a dictionary for sense similarity measure
... language data have to cope with the numerous different senses possessed by every lexical item: ma- chine translation, information retrieval, infor- mation extraction ...supervised sense clustering) or by ... See full document
7
Word Sense Disambiguation using a Bidirectional LSTM
... a way to represent words as real valued vectors in a semantically meaningful ...for Word Representation (GloVe), introduced by Pennington et ...statistics. Word embed- dings are trained in an ... See full document
6
Multilingual Word Sense Disambiguation Using Wikipedia
... the data from English into several other ...the word alignments. Given a target word in an English sentence, we used the word align- ments to identify the position of the target word ... See full document
9
Using Parallel Corpora for Word Sense Disambiguation
... lowing way. Initially, each word in each language in the word-aligned parallel corpus is given a separate, unique ...Two data structures, an ’open’ and a ’closed’ list are ...a word ... See full document
6
Is Three the Optimal Context Window for Memory-Based Word Sense Disambiguation?
... specific word class, namely adjectives as shown in table ...the data for adjectives is not repre- sentative enough, since we only have 5 instances and, thus, more data is needed in order to be sure ... See full document
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Towards Dynamic Word Sense Discrimination with Random Indexing
... appearing word senses, word senses that depend on the actual usage of a term in a cor- pus or a ...as Word Sense Induction or Word Sense Discrimina- tion (Sch¨utze, ...input ... See full document
8
Enriching Wordnet for Word Sense Disambiguation
... the sense bag with more information leading to higher degrees of overlap for the most appropriate sense of a word in question, thereby achieving better quality word sense disambiguation ... See full document
6
Word Sense Disambiguation using Conceptual Density
... Word Sense Disambiguation using Conceptual Density Word Sense Disambiguation using Conceptual Density Eneko Agirre* Lengoaia eta Sistema Informatikoak saila Euskal Herriko Universitatea p k 649, 20080[.] ... See full document
7
Word Sense Disambiguation Using Statistical Methods
... Probabilities of French translations Figure 5: Senses for the English word cent Pleased with these results, we incorporated sense-assignment questions for the 500 most common English wor[r] ... 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 Induction using Cluster Ensemble
... For example, features based on global window might perform well when instances are shot, whereas a feature weighting method for this task should be invariant to the all the WSI corpus. Therefore it is widely accepted ... See full document
8
Determining Word Sense Dominance Using a Thesaurus
... for sense disambiguation with a Bayesian ...WCCM using sim- ple bootstrapping techniques, used all the words that co-occur with a category, and proposed four new methods to determine sense dominance— ... See full document
8
Automatic Word Sense Discrimination
... Similarity in Word Space is based on second-order co-occurrence: two tokens or contexts of the ambiguous word are assigned to the same sense cluster if the words they co-occur with in tu[r] ... See full document
28
Unsupervised Word Sense Disambiguation Using Bilingual Comparable Corpora
... The disparity of topical coverage between the cor- pora of two languages and the insufficient coverage of the bilingual dictionary also cause a lot of pairs of re- lated words not to be aligned with any pair of related ... See full document
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