vector space models
Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models
... While vector space representations for indi- vidual words are well-understood, there remains much uncertainty about how to compose vector space representations for phrases out of their com- ...
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Evaluating Context Selection Strategies to Build Emotive Vector Space Models
... In this paper we compare different context selection approaches to improve the creation of Emotive Vector Space Models (VSMs). The system is based on the results of an existing approach that showed ...
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Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality
... In recent years, there has been a growing interest in algorithms that learn a continuous representation for words, phrases, or documents. For instance, one can see latent semantic analysis and latent Dirichlet allocation ...
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Multi Prototype Vector Space Models of Word Meaning
... Current vector-space models of lexical seman- tics create a single “prototype” vector to rep- resent the meaning of a ...single vector is ...context-dependent vector ...
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Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition
... semantics, Vector Space Models (VSMs) of words are built either from topical information ...composed vector represen- tation of a phrase from the brain activity of a human subject reading that ...
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Vector space models for PPDB paraphrase ranking in context
... the vector-space models for each target word instance is to rank the contents of the corresponding paraphrase set (which contains all the substitution candidates available for the target in ...
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Measuring Word Relatedness Using Heterogeneous Vector Space Models
... individual vector space models, as well as combin- ing these models using the averaged cosine ...these models, the performance is improved substan- ...based models work only ...
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Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality
... continuous space allows for the design of algorithms that are not plagued with the local minima issues that discrete latent space models ...behind vector space models from the ...
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Vector Space Models for Phrase based Machine Translation
... of vector space models (VSMs) to the standard phrase-based machine translation ...are models based on continuous word representations embed- ded in a vector ...
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Applicative structure in vector space models
... Section 2 offers a method to treat antonymy in continuous vector space models (CVSMs). Sec- tion 3 describes a new embedding, 4lang, obtained by spectral clustering from the definitional frame- work ...
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Vector Space Models for Scientific Document Summarization
... of vector space models to- gether with a variety of algebraic dimensionality reduction techniques (LSA, LDA, and NNMF) to summarize multi-lingual ...known vector space model for text, ...
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Post hoc Manipulations of Vector Space Models with Application to Semantic Role Labeling
... specific vector space representations, post-hoc methods to manipulate the vector spaces without retraining are ...used vector similarities to automatically expand the small training set to ...
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Ontologically Grounded Multi sense Representation Learning for Semantic Vector Space Models
... expressive models that can jointly learn other useful parameters – such as context vectors in the case of ...MLE models, and is also empiri- cally ...
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Discovering Stylistic Variations in Distributional Vector Space Models via Lexical Paraphrases
... feature vector in word2vec spaces or their ...(W2V) models of blogs corpus with different space sizes (dimensionality=1-10, 15, 20, 25, 30, 35, 40, 45, 50, 100, 150, 200, 250, 300, 350, 400, 450, ...
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Unifying Bayesian Inference and Vector Space Models for Improved Decipherment
... Both approaches have been shown to improve quality of MT systems for domain adaptation (Daum´e and Jagarlamudi, 2011; Dou and Knight, 2012; Irvine et al., 2013) and low density lan- guages (Irvine and Callison-Burch, ...
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Crosslingual and Multilingual Construction of Syntax Based Vector Space Models
... appropriate models for many phenomena in lexical ...simplest models, which are based solely on the English Distributional Memory (DM) resource and a translation lexicon, already beat monolingual DMs in ...
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Evaluating vector space models using human semantic priming results
... Most previous work has modeled small prim- ing datasets. By contrast, we follow Mandera et al. (2016) in taking advantage of the online database of the Semantic Priming Project (SPP), which compiles priming data from 768 ...
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Vector space models for evaluating semantic fluency in autism
... Figure 1 shows two semantic fluency responses, one produced by a child with ASD and one by a child with TD, with plots indicating the cosine similarities between adjacent words derived from both the LSA and word2vec ...
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Extractive Summarization using Continuous Vector Space Models
... continuous vector representations for se- mantically aware representations of sen- tences as a basis for measuring similar- ...word vector representations for automatic ...
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The Role of Syntax in Vector Space Models of Compositional Semantics
... of vector space representations of sentential semantics and the transparent interface between syntax and semantics provided by Combinatory Categorial Grammar to introduce Com- binatory Categorial ...
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