[PDF] Top 20 Evaluation of Word Vector Representations by Subspace Alignment
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Evaluation of Word Vector Representations by Subspace Alignment
... verbs. Word similarity is computed using co- sine similarity between two words and the perfor- mance of word vectors is computed by Spearman’s rank correlation between the rankings produced by vector ... See full document
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Find the word that does not belong: A Framework for an Intrinsic Evaluation of Word Vector Representations
... intrinsic evaluation of word vector space ...of vector space models not fully addressed to ...state-of-the-art word embeddings perform reasonably well in the task but are still far from ... See full document
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Correlation based Intrinsic Evaluation of Word Vector Representations
... of word vector models and, consequently, improvement of the target ...intrinsic evaluation that approximates a range of related downstream tasks ...a word vec- tor model, without actually ... See full document
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Non distributional Word Vector Representations
... Table 3 shows the performance of different word vector types on the evaluation tasks. It can be seen that although Skip-Gram, Glove & LSA perform better than linguistic vectors on WS-353, the ... See full document
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Retrofitting Word Vectors of MeSH Terms to Improve Semantic Similarity Measures
... utilizes vector word representation and the linkage information in an ontology or ...retrofitting vector representations with additional ontology or taxonomy information, we can gener- ate ... See full document
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Unsupervised Topic Modeling for Short Texts Using Distributed Representations of Words
... distributed representations of words. We model the low-dimensional seman- tic vector space represented by the dense distributed representations of words using Gaussian mixture models (GMMs) whose ... See full document
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Conditional Generators of Words Definitions
... the evaluation task. In definition modeling vector representations of words are used for conditional generation of corresponding word ...quality word embedding should contain all useful ... See full document
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Improving Vector Space Word Representations Using Multilingual Correlation
... common vector space such that translation pairs (as deter- mined by automatic word alignments) should be maximally correlated ...dard evaluation tasks that we use to measure the quality of the ... See full document
10
Phonetic Vector Representations for Sound Sequence Alignment
... a vector which is then decoded into an output ...dense vector representations with a smaller number of ...useful representations for IPA ...the representations build for each IPA-token ... See full document
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Graph Based Word Alignment for Clinical Language Evaluation
... Much of the previous work in applying automated analysis of unannotated transcripts of narratives for diagnostic purposes has focused not on evaluating properties specific to narratives but rather on using narratives as ... See full document
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Incorporating Relational Knowledge into Word Representations using Subspace Regularization
... Rank-1 subspace regularization can also be motivated from the fact that word embeddings are able to capture some linguistic regulari- ties (Mikolov et ...the vector space. For example, the dif- ... See full document
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Proceedings of the 1st Workshop on Evaluating Vector Space Representations for NLP
... current evaluation options is their lack of diversity; despite the large number of intrinsic benchmarks (23 by some counts), and their many differences in size, quality, and domain, the majority of them focus on ... See full document
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Intrinsic Subspace Evaluation of Word Embedding Representations
... this word have a particular meaning? A representation can fail on similarity judgement computations because less frequent senses occupy a small part of the capacity of the representa- tion and therefore have ... See full document
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Word to word alignment strategies
... Word alignment quality is usually measured in terms of precision and ...with word alignment arises with links between MWUs that cause partially correct ... See full document
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Exploring Compositional Architectures and Word Vector Representations for Prepositional Phrase Attachment
... original word vectors in several important directions: enriching word vectors with semantic and syntactic knowledge resources, relearning them by backpropagating errors from su- pervised data, and using ... See full document
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A Comparison of Context sensitive Models for Lexical Substitution
... for word sense disambiguation systems (McCarthy and Navigli, 2007), in recent works it is mainly seen as a way of evaluating the in-context lexical inference capacity of vector-space models without ... See full document
12
Financial Keyword Expansion via Continuous Word Vector Representations
... This paper proposes to apply the contin- uous vector representations of words for discovering keywords from a financial sen- timent lexicon. In order to capture more keywords, we also incorporate syntactic ... See full document
6
CSE: Conceptual Sentence Embeddings based on Attention Model
... and word topics, and latent topic model suffer ex- tremely from the sparsity of the ...take word order into ...topical word embeddings of each word in this sentence in TWE, which lim- its its ... See full document
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Tweet2Vec: Character Based Distributed Representations for Social Media
... model requires no language specific preprocessing and can be extended to other languages. For fu- ture work, one natural extension would be to use a character-level decoder for predicting the hash- tags. This will allow ... See full document
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Word-Transliteration Alignment
... The alternative to on-the-fly (back) machine transliteration is simple lookup in an extensive list auto- matically acquired from parallel corpora. Most instances of (back) transliteration of proper names can often be ... See full document
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