[PDF] Top 20 Unsupervised Translation Sense Clustering
Has 10000 "Unsupervised Translation Sense Clustering" found on our website. Below are the top 20 most common "Unsupervised Translation Sense Clustering".
Unsupervised Translation Sense Clustering
... In addition to the features described in Lin and Wu (2009), we introduce features from a bilingual par- allel corpus that encode reverse-translation informa- tion from the source-language (Spanish or Japanese in ... See full document
10
Unsupervised Relation Discovery with Sense Disambiguation
... possible sense per ...into sense clusters using local and global features. We merge these sense clus- ters into semantic relations using hierarchical agglomerative ...a clustering method that ... See full document
9
Sense Aware Statistical Machine Translation using Adaptive Context Dependent Clustering
... a sense graph from WordNet (Agirre and Soroa, ...MaxEnt-based translation model for English-Portuguese ...the sense graph, WordNet pro- vides also textual information such as sense def- ... See full document
10
Unsupervised Word Sense Disambiguation Using Bilingual Comparable Corpora
... its translation form a non-aligned (comparable) ...a translation matrix that maximizes the distance between the co-occurrence matrix of the first language and that of the second lan- ...which sense ... See full document
7
MUSE: Modularizing Unsupervised Sense Embeddings
... of sense selection. First, the deci- sion of a word sense is Markov: taking the whole corpus into consideration is not more helpful than a handful of necessary local ...selecting sense identity, ... See full document
11
Word Sense Clustering and Clusterability
... using translation vectors built from a multilingual ...the translation or paraphrase data or examine the findings in terms of ...through translation and paraphrase annotations; in the future, we will ... See full document
31
A Sense Topic Model for Word Sense Induction with Unsupervised Data Enrichment
... 2010). Sense inventories also impose a fixed sense gran- ularity for each ambiguous word, which may not match the ideal granularity for the task of ...machine translation and information retrieval ... See full document
14
Unsupervised Word Sense Disambiguation with Multilingual Representations
... using translation for WSD, we present several exam- ples in Table ...“asset” sense of capital, the incor- rect sense assignment would ...the sense of ... See full document
5
Models and Training for Unsupervised Preposition Sense Disambiguation
... Reliable disambiguation of words plays an impor- tant role in many NLP applications. Prepositions are ubiquitous—they account for more than 10% of the 1.16m words in the Brown corpus—and highly ambiguous. The Preposition ... See full document
6
Multigraph Clustering for Unsupervised Coreference Resolution
... Coreference resolution is the task of determining which mentions in a text refer to the same en- tity. With the advent of machine learning and the availability of annotated corpora in the mid 1990s the research focus ... See full document
8
Factored Translation with Unsupervised Word Clusters
... word clustering models, factored corpora, language models, as well as training, optimization and eval- uation of the various models was a rather involved, yet repetitive process, we took a stab at making a GNU ... See full document
5
Sense Clustering Using Wikipedia
... Coarser sense inventories also make it eas- ier to identify synonyms or translations of selected words in context, which can lead to improvements in information retrieval (Zhong and Ng, 2012), se- mantic indexing ... See full document
8
Evaluating Unsupervised Ensembles when applied to Word Sense Induction
... Word Sense Induction models define word senses in terms of the distributional hypothesis, whereby the meaning of a word can be defined by the surround- ing context (Haris, ...by clustering. These similar ... See full document
6
Contextual Modeling for Meeting Translation Using Unsupervised Word Sense Disambiguation
... the translation was pragmati- cally ...language translation, the goal of this study is not to analyze the impact of speech-specific phenomena on translation performance (which, as discussed in ... See full document
9
Structured Generative Models for Unsupervised Named Entity Clustering
... entity clustering is a classic task in NLP, and one for which both supervised and semi-supervised systems have excellent performance (Mikheev et ...fully unsupervised system (using no “seed rules” or ... See full document
9
Lightly Supervised Training for Hierarchical Phrase Based Machine Translation
... the unsupervised data and to jointly extract phrases from the unified parallel data (after having trained word alignments for the unsupervised bitexts as ...the unsupervised part of the training ... See full document
6
SVD and Clustering for Unsupervised POS Tagging
... While supervised approaches are able to solve the part-of-speech (POS) tagging problem with over 97% accuracy (Collins 2002; Toutanova et al. 2003), unsupervised algorithms perform con- siderably less well. These ... See full document
5
Grounded Word Sense Translation
... similar task but focused at the word level and only at ambiguous words. In MLT, the objective is to correctly translate each ambiguous word in the En- glish source sentence into a corresponding word in the target ... See full document
8
Unsupervised Bilingual Word Embedding Agreement for Unsupervised Neural Machine Translation
... Unsupervised bilingual word embedding (UBWE), together with other technologies such as back-translation and denoising, has helped unsupervised neural machine translation (UNMT) achieve ... See full document
11
Unsupervised Attention Embedding for Document Clustering
... existing clustering approaches suffer from three main issues when dealing with text: (1) using meaningless data space, which lead to a reduced density of similarity between documents and fail to compress all the ... See full document
6
Related subjects