[PDF] Top 20 A Systematic Study of Semantic Vector Space Model Parameters
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A Systematic Study of Semantic Vector Space Model Parameters
... that semantic similarity studies have been overfit- ting to their idiosyncracies, so in this study we evaluate on a variety of datasets: in addition to WordSim353 (W353) and TOEFL, we also use the ... See full document
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Improving the relevancy of document search using the multi term adjacency keyword order model
... This study introduced an enhanced relevance ranking technique for information retrieval based on vector space ...proposed model focuses only on precision that favors to system which retrieves ... See full document
10
A Generative Model of Vector Space Semantics
... new model for vector space representations of word and phrase mean- ing, by providing an explicit probabilistic process by which natural language expressions are gener- ated from vectors in a ... See full document
9
Robust Co occurrence Quantification for Lexical Distributional Semantics
... a systematic study of co- occurrence quantification focusing on the se- lection of parameters presented in Levy et ...high-dimensional vector spaces, and show that with appropriate parameter ... See full document
7
Evaluating vector space models using human semantic priming results
... to study the effects of context on word ...that vector space model representations of preceding context and target words can predict N400 ampli- tude (Parviz et ... See full document
6
The Lifted Matrix Space Model for Semantic Composition
... to semantic composition gener- ally seen in formal linguistics, and have shown empirical improvements over comparable se- quence models by doing ...as model dimension or vocabulary size ... See full document
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Regular polysemy: from sense vectors to sense patterns
... like semantic shifts (lamb can denote either ANIMAL or FOOD), metonymy (church can denote either ORGANIZATION or LOCATION) and metaphor ...to model regular polysemy in semantic vector ... See full document
5
Paraphrase Assessment in Structured Vector Space: Exploring Parameters and Datasets
... SVS model is to treat the interpretation of a word in context as guided by expecta- tions about typical ...a model of word meaning is motivated both on cognitive and linguistic ...in semantic ... See full document
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Documents and Dependencies: an Exploration of Vector Space Models for Semantic Composition
... a systematic study of comple- mentarity of topical (Document) and type (Depen- dency) features in Vector Space Model (VSM) for semantic composition of adjective-noun ... See full document
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Vector Space Semantic Parsing: A Framework for Compositional Vector Space Models
... present vector space semantic parsing (VSSP), a general framework for building compositional models of vector space ...and semantic types rep- resenting vectors and functions on ... See full document
10
Finding Non Arbitrary Form Meaning Systematicity Using String Metric Learning for Kernel Regression
... and semantic vectors derived from a distributional se- mantic model, the Nadaraya-Watson estimator can estimate the position in the semantic vector space for each word in the ...Context ... See full document
10
The Study of Information Retrieval
... of study information retrieval might be defined as Information retrieval (IR) is finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within large ... See full document
5
What Do We Learn from Word Associations? Evaluating Machine Learning Algorithms for the Extraction of Contextual Word Meaning in Natural Language Processing
... Keywords: Machine Learning; Algorithms; Natural Language Processing, Deep Learning, Vector 29.. Space Models, Semantic Similarity, Distributional Semantics, Latent Semantic Analys[r] ... See full document
21
Extrofitting: Enriching Word Representation and its Vector Space with Semantic Lexicons
... the vector space as well as agree and disagree should be mapped apart, although they occur on a very similar ...use semantic lexicons (Faruqui et ...fixed vector space (it will be ... See full document
6
Measuring Word Relatedness Using Heterogeneous Vector Space Models
... the semantic relatedness of words is a fundamental problem in natural language process- ing and has many useful applications, including textual entailment, word sense disambiguation, in- formation retrieval and ... See full document
5
Feature2Vec: Distributional semantic modelling of human property knowledge
... on semantic cog- ...tor space models of word meaning over large ...tributional semantic space, which adapts the word2vec architecture to the task of modelling concept ...gle semantic ... See full document
7
A Quantum Theoretic Approach to Distributional Semantics
... of semantic space models with quantum the- ory are due to Aerts and Czachor (2004) and Bruza and Cole ...Latent Semantic Analysis (Landauer and Du- mais, 1997) and the Hyperspace Analog to Lan- guage ... See full document
11
Lexical Transfer Using a Vector Space Model
... A bilingual dictionary consists of rules that map a part of the representation of a source sentence to a target representation by taking grammatical differences (such as the word order between the source and target ... See full document
7
Design and analysis of a general vector space model for data classification in Internet of Things
... optical character recognition. Joachims [36] explores the use of support vector machines (SVMs) for learning text classifiers from examples. It analyzes the particular prop- erties of learning with text data and ... See full document
10
Vector space calculation of semantic surprisal for predicting word pronunciation duration
... the semantic surprisal model when trained on more domain-general ...our semantic model, we use a ran- domly selected 1% (by sentence) of the English Gigaword ...the model against the ... See full document
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