[PDF] Top 20 A Structured Vector Space Model for Word Meaning in Context
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A Structured Vector Space Model for Word Meaning in Context
... The SVS scheme we have proposed incorporates syntactic information in a more general manner than previous models, and thus addresses the issues we have discussed in Section 1. Since the representation retains individual ... See full document
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Latent Vector Weighting for Word Meaning in Context
... of word meaning in ...factorization model based on non-negative ma- trix factorization, in which words, together with their window-based context words and their dependency relations, are ... See full document
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A comparison of models of word meaning in context
... In this paper, we have compared three related vec- tor space models of word meaning in context. We have reformulated the models and showed that they are in fact very similar. We also showed ... See full document
5
Measuring Word Meaning in Context
... a word and argues that sense distinction only makes sense with respect to a given ...of word meaning such as the Generative Lexicon (Pustejovsky 1991) also draw attention to the subtle, yet reliable, ... See full document
44
Modeling Word Meaning in Context with Substitute Vectors
... of word meaning is the choice of context ...target word type to derive its representation. More recent models of word meaning in context typically bias such a word ... See full document
11
Exemplar Based Models for Word Meaning in Context
... a model of word meaning in context, since they do not have to rely on fixed sets of dictionary sense with their well-known problems (Kilgarriff, 1997; McCarthy and Navigli, ...the ... See full document
6
Word Meaning in Context: A Simple and Effective Vector Model
... Gold standard. We evaluate our model on the SemEval 2007 Coarse-grained English All-words Task (Navigli et al., 2007) test set. The test set consists of 5,377 words of running text from five documents from ... See full document
10
Word Meaning and Context: a Critical Examination of Contrasting Perspectives
... immediate disadvantage compared to the actual participants of any communicative exchange under formal scrutiny; chiefly because 'the linguistic element' is necessarily recontextualised prior to any formal analysis. ... See full document
114
The neuro-cognitive representation of word meaning resolved in space and time.
... The assumption that concepts are not represented in unitary nodes (as suggested by Quillian), but instead in a distributed fashion, is at the core of another family of models, that of distributional ones, also referred ... See full document
338
Implementation Svm To Solve Multiple Meaning Of Word Problem
... resolve meaning of given word with the help of an algorithm selected and approached used to decide meaning ...disambiguated word along with feature and POS “part of ...correct meaning ... See full document
5
Measuring Distributional Similarity in Context
... obtain word meanings in ...several vector composition op- erations for representing short sentences (consist- ing of intransitive verbs and their ...on vector addition (Landauer and Du- mais, 1997; ... See full document
11
What Is Word Meaning, Really? (And How Can Distributional Models Help Us Describe It?)
... in space. However, vector space models have mostly been used to represent the meaning of a word in isolation: The vector for a word is com- puted by summing over all its ... See full document
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Looking at word meaning An interactive visualization of Semantic Vector Spaces for Dutch synsets
... To illustrate the information that is avail- able through this visualization, we discuss the weighted chart for the concept C OMPUTER SCREEN (Figure 1 shows a screen cap, but we strongly advise to look at the interactive ... See full document
9
Multi Prototype Vector Space Models of Word Meaning
... ditionally, word types are represented by a sin- gle vector of contextual features derived from co- occurrence information, and semantic similarity is computed using some measure of vector distance ... See full document
9
A Structured Vector Space Model for Hidden Attribute Meaning in Adjective Noun Phrases
... as structured vector ...to word meaning, but are noticeably extended to capture meaning on the phrase ...single word co- occurrences as dimensions of semantic ...compositional ... See full document
9
Nonlocal Language Modeling based on Context Co occurrence Vectors
... A reduced vector space model calculated from co-occurrences of word pairs provides word co-occurrence vectors.. T h e sum of word co- occurrence vectors represents tile context of a docu[r] ... See full document
7
Improving Cohesion Measurement for Object Oriented Systems in Java
... semi structured data. The structured data is destined primarily for the parsers, while the unstructured information (that is, the comments and identifiers) is destined primarily to the human ...a ... See full document
8
CONTEXT BASED INTER STRUCTURAL MINING ON SEMI STRUCTURED DATA USING VECTOR SPACE MODEL
... The context aware is most important in any XML ...the context is different. Therefore context is ...the context is set through the ...is vector space model , in which all ... See full document
5
Neural Vector Conceptualization for Word Vector Space Interpretation
... language space and is capa- ble of modeling non-linear relations between lan- guage instances and ...NLP model that we trained on an instance-concept ground truth that could be replaced by another ... See full document
7
WiC: the Word in Context Dataset for Evaluating Context Sensitive Meaning Representations
... using word embed- dings and computes embedding for each cluster ...learning word and sense embeddings, pro- ducing a shared vector space of words and senses as a ...the context vec- ... See full document
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