[PDF] Top 20 Deep Multilingual Correlation for Improved Word Embeddings
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Deep Multilingual Correlation for Improved Word Embeddings
... Word embeddings have been found useful for many NLP tasks, including part-of-speech tagging, named entity recognition, and pars- ...Adding multilingual context when learn- ing embeddings can ... See full document
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Multilingual Models for Compositional Distributed Semantics
... learning multilingual word embeddings using parallel data in conjunction with a multilingual ob- jective function for compositional vector ...to multilingual joint-space ... See full document
11
Using bilingual word embeddings for multilingual collocation extraction
... tion with a base equivalent is found, we com- pute the cosine distance between both collocates (“tremendo” versus “little”, “deep”, “huge”, and “fine”) and select them as potential candidates if their similarity ... See full document
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Word Embeddings and Its Application in Deep Learning
... II. WORD EMBEDDINGS AND DEEP LEARNING Word Embedding is the robust solution for many NLP ...of word embedding relies on converting space vector representation into a dense continuous ... See full document
5
Joint learning of frequency and word embeddings for multilingual readability assessment
... The data driven approach treats readability as- sessment as a machine learning problem, that is to automatically learn the mapping from documents to difficulty levels based on training examples (Si and Callan, 2001; ... See full document
5
Learning Multilingual Word Embeddings Using Image Text Data
... lingual embeddings (cf. Section 2). These meth- ods take monolingual embeddings learned using existing methods and align them post-hoc in a shared embedding ...monolingual embeddings, first noticed ... See full document
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GSI UPM at SemEval 2019 Task 5: Semantic Similarity and Word Embeddings for Multilingual Detection of Hate Speech Against Immigrants and Women on Twitter
... As future work, several lines of work could be addressed. Firstly, we plan to implement deep learning architectures which have shown to obtain better results in previous research (Zhang and Luo, 2018; Zhang et ... See full document
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Semantic Information Extraction for Improved Word Embeddings
... improve word embed- dings by drawing on the idea that certain contexts exhibit more semantically meaningful information than ...on word defini- tions and synonyms, as well as on lists and enumer- ...final ... See full document
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Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach
... metric incorporates the feature correlation infor- mation from the given training data. This allows for a more effective similarity comparison of language embeddings (than the cosine similarity). In fact, ... See full document
14
GlobalTrait: Personality Alignment of Multilingual Word Embeddings
... called word embeddings, as ...or multilingual word embeddings try to cap- ture such semantic information of words across two or more languages, such that the words that have similar ... See full document
8
Domain Adapted Word Embeddings for Improved Sentiment Classification
... Generic word embeddings are trained on large-scale generic corpora; Domain Spe- cific (DS) word embeddings are trained only on data from a domain of inter- ...cific embeddings. The ... See full document
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Domain Adapted Word Embeddings for Improved Sentiment Classification
... monolingual word embed- dings across data sets in different application do- mains/contexts for the purpose of a given down- stream task such as sentiment ...ing word embeddings across different ... See full document
9
Improving Vector Space Word Representations Using Multilingual Correlation
... How can we exploit information like this when constructing VSMs? We propose a technique that first constructs independent VSMs in two lan- guages and then projects them onto a common vector space such that translation ... See full document
10
Multilingual Training of Crosslingual Word Embeddings
... tilingual word embeddings using set of bilingual ...building multilingual word ...canonical correlation analysis (CCA) for multiple languages using English as the ...bilingual ... See full document
11
Learning Unsupervised Multilingual Word Embeddings with Incremental Multilingual Hubs
... languages, multilingual methods have been ...with multilingual co- occurrence counts weighted by probabilistic dictio- ...the multilingual extension of the method of Faruqui and Dyer (2014): Using ... See full document
13
Deep neural model with enhanced embeddings for pharmaceutical and chemical entities recognition in Spanish clinical text
... concept embeddings and analyze why its performance is lower than the medi- cal word ...train word embeddings obtained from mul- tiple multilingual biomedical corpus to obtain ... See full document
9
Multilingual segmentation based on neural networks and pre trained word embeddings
... As mentioned before, the segmentation task is the first elemental stage in discourse parsing. Some English parsers (Joty et al., 2015; Feng and Hirst, 2014; Ji and Eisenstein, 2014) and Por- tuguese parsers (Pardo and ... See full document
8
Beyond Bilingual: Multi sense Word Embeddings using Multilingual Context
... ing multiple languages. Consider the case of using French and Spanish contexts to disambiguate the financial sense of the English word bank. In this case, the (financial) sense vector of bank will be used to ... See full document
10
An Automatic Learning of an Algerian Dialect Lexicon by using Multilingual Word Embeddings
... are included into CWL. Where N(x) is the occurrence of x, α is set empirically to 1000 and S is a function that en- codes phonetically a word. The constraint represented by S takes into account the variability of ... See full document
7
Symmetric Pattern Based Word Embeddings for Improved Word Similarity Prediction
... exploit word co- occurrence ...the word vector ...in word representation learning (Bengio et ...learn word vectors that maximize a language model objective, thus capturing the tendencies of ... See full document
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