Distributional Semantics 2019


Notes:

Linguistic items with similar distributions have similar meanings.

  • Distributional semantic

Resources:

  • s-space .. highly-scalable library for designing new distributional semantics algorithms

Wikipedia:

References:

See also:

JoBimText


A generalised quantifier theory of natural language in categorical compositional distributional semantics with bialgebras
J Hedges, M Sadrzadeh – Mathematical Structures in Computer …, 2019 – cambridge.org
Categorical compositional distributional semantics is a model of natural language; it combines the statistical vector space models of words with the compositional models of grammar. We formalise in this model the generalised quantifier theory of natural language …

Don’t Blame Distributional Semantics if it can’t do Entailment
M Westera, G Boleda – arXiv preprint arXiv:1905.07356, 2019 – arxiv.org
Distributional semantics has had enormous empirical success in Computational Linguistics and Cognitive Science in modeling various semantic phenomena, such as semantic similarity, and distributional models are widely used in state-of-the-art Natural Language …

Graded hyponymy for compositional distributional semantics
D Bankova, B Coecke, M Lewis… – Journal of Language …, 2019 – jlm.ipipan.waw.pl
The categorical compositional distributional model of natural language provides a conceptually motivated procedure to compute the meaning of a sentence, given its grammatical structure and the meanings of its words. This approach has outperformed other …

Similarity is closeness: Using distributional semantic spaces to model similarity in visual and linguistic metaphors
M Bolognesi, L Aina – Corpus Linguistics and Linguistic Theory, 2019 – degruyter.com
The semantic similarity that characterizes two terms aligned in a metaphor is here analysed through a corpus-based distributional semantic space. We compare and contrast two samples of metaphors, representative of visual and linguistic modality of expressions …

Distributional semantics as a source of visual knowledge
M Lewis, M Zettersten… – Proceedings of the …, 2019 – National Acad Sciences
In PNAS Kim et al.(1) detail congenitally blind individuals’ extensive knowledge of the visual appearance of animals. This is exciting and important work speaking directly to long-standing questions about the role of direct perceptual experience in semantic knowledge …

The role of negative information in distributional semantic learning
BT Johns, DJK Mewhort, MN Jones – Cognitive science, 2019 – Wiley Online Library
Distributional models of semantics learn word meanings from contextual co?occurrence patterns across a large sample of natural language. Early models, such as LSA and HAL (Landauer & Dumais, 1997; Lund & Burgess, 1996), counted co?occurrence events; later …

A comprehensive study of the parameters in the creation and comparison of feature vectors in distributional semantic models
A Dobó, J Csirik – Journal of Quantitative Linguistics, 2019 – Taylor & Francis
Measuring the semantic similarity and relatedness of words can play a vital role in many natural language processing tasks. Distributional semantic models computing these measures can have many different parameters, such as different weighting schemes, vector …

When does abstraction occur in semantic memory: insights from distributional models
MN Jones – Language, Cognition and Neuroscience, 2019 – Taylor & Francis
… IN, USA ABSTRACT Abstraction is a core principle of Distributional Semantic Models (DSMs) that learn semantic representations for words by applying dimensional reduction to statistical redundancies in language. Although …

A Framework for Distributional Formal Semantics
NJ Venhuizen, P Hendriks, MW Crocker… – … Workshop on Logic …, 2019 – Springer
Formal semantics and distributional semantics offer complementary strengths in capturing the meaning of natural language … Abstract. Formal semantics and distributional semantics offer complementary strengths in capturing the meaning of natural language …

Distributional Semantics of Clinical Words
V Krishna, S Mujjiga, K Chakravarthil… – 2019 IEEE 13th …, 2019 – ieeexplore.ieee.org
Word embeddings are the distributed representation of the words in numerical form. Recent research in word embeddings shows the importance of using them in deep learning algorithms. Word embeddings are commonly leveraged as feature inputs to many deep …

Cross-topic distributional semantic representations via unsupervised mappings
E Briakou, N Athanasiou, A Potamianos – arXiv preprint arXiv:1904.05674, 2019 – arxiv.org
In traditional Distributional Semantic Models (DSMs) the multiple senses of a polysemous word are conflated into a single vector space representation. In this work, we propose a DSM that learns multiple distributional representations of a word based on different topics …

Distributional semantics of objects in visual scenes in comparison to text
T Lüddecke, A Agostini, M Fauth, M Tamosiunaite… – Artificial Intelligence, 2019 – Elsevier
The distributional hypothesis states that the meaning of a concept is defined through the contexts it occurs in. In practice, often word co-occurrence and proximity are analyzed in text corpora for a given word to obtain a real-valued semantic word vector, which is taken to (at …

Deep reinforcement learning with distributional semantic rewards for abstractive summarization
S Li, D Lei, P Qin, WY Wang – arXiv preprint arXiv:1909.00141, 2019 – arxiv.org
Deep reinforcement learning (RL) has been a commonly-used strategy for the abstractive summarization task to address both the exposure bias and non-differentiable task issues. However, the conventional reward Rouge-L simply looks for exact n-grams matches …

What are we learning from language? Associations between gender biases and distributional semantics in 25 languages
M Lewis, G Lupyan – 2019 – psyarxiv.com
Cultural stereotypes such as the idea that men are more suited for paid work while women for taking care of the home and family may contribute to gender imbalances in STEM fields (eg, Leslie, Cimpian, Meyer, & Freeland, 2015) and other undesirable gender disparities …

Distributional semantic representations predict high-level human judgment in seven diverse behavioral domains
R Richie, W Zou, S Bhatia – Proceedings of the 41st …, 2019 – cogsci.mindmodeling.org
The complex judgments we make about the innumerable objects in the world are made on the basis of our representation of those objects. Thus a model of judgment should specify (a) our representation of the many objects in the world, and (b) how we use this knowledge for …

Comparison of the best parameter settings in the creation and comparison of feature vectors in distributional semantic models across multiple languages
A Dobó, J Csirik – IFIP International Conference on Artificial Intelligence …, 2019 – Springer
Measuring the semantic similarity and relatedness of words is important for many natural language processing tasks. Although distributional semantic models designed for this task have many different parameters, such as vector similarity measures, weighting schemes and …

A transportable distributional semantics architecture
S Barzegar – 2019 – archivesearch.library.nuigalway.ie
Distributional semantics is built upon the assumption that the context surrounding a given word in text provides important information about its meaning (Distributional hypothesis). A rephrasing of the distributional hypothesis states that words that occur in similar contexts …

Controlling Distributional Semantics and Unified Modeling
G Wade, S Murray, J Fuller – Computer Science and Information …, 2019 – csitpub.org
Unified estimation algorithms have led to many structured advances, including Component-based software engineering and randomized algorithms. In fact, few computational biologists would disagree with the understanding of decision tables, which embodies the …

Exploring Distributional Semantics Using Compact Modalities
M Schneider, D Hurst, L Nelson – Computer Science and Information …, 2019 – csitpub.org
In recent years, much research has been devoted to the evaluation of congestion control; unfortunately, few have improved the compelling unification of rapid prototyping and software inspections. Given the trends in scalable archetypes, cyberinformaticians …

Insulating Distributional Semantic Models from Catastrophic Interference
WM Mannering, MN Jones – earbmc.sitehost.iu.edu
Predictive neural networks, such as word2vec, have seen impressive recent popularity as an architecture to learn distributional semantics in the fields of machine learning and cognitive science. They are particularly popular because they learn continuously, making them more …

Studying Checksums and Distributional Semantics
M Richardson – Systems and Software Engineering Publication, 2019 – ssepublication.com
Many mathematicians would agree that, had it not been for semaphores, the exploration of thin clients might never have occurred. In fact, few security experts would disagree with the understanding of fault-tolerant mesh networks, demonstrates the appropriate importance of …

Negated Adjectives and Antonyms in Distributional Semantics: not similar?
L Aina, R Bernardi, R Fernández – Italian Journal of Computational …, 2019 – narcis.nl
We investigate the relation between negated adjectives and antonyms pairs in English (eg, not cold vs. hot-cold) using Distributional Semantics. We build vector representations of a set of antonyms and their negations on the basis of their contexts of use, and compare the …

Architecting XML and Distributional Semantics Using HERT
C Schwartz, P Cortez, J Ibarra, R Woodard – Software engineering and …, 2019 – secsjr.org
Unified lean methodologies have led to many compelling advances, including active networks and Markov models. After years of significant research into write-back caches, we confirm the understanding of Software Management, demonstrates the practical importance …

Towards the Refinement of Distributional Semantics
J Bishop, D Smith – International Journal of Software Systems Research …, 2019 – ssysrm.org
Recent advances in rule-based epistemologies and multimodal information offer a viable alternative to checksums. Given the current status of service-oriented theory, cryptographers daringly desire the evaluation of decision support systems. Our focus in our research is not …

Contributions of distributional semantics to the semantic study of French morphologically derived agent nouns
M Wauquier, N Hathout… – Mediterranean …, 2019 – mmm.library.upatras.gr
The Distributional Hypothesis, proposed by Harris (1954), Firth (1957), and Miller and Charles (1991) among others, states that the semantic proximity between words is reflected in the proximity of their distribution. This principle has been captured in distributional semantics models …

Gaussianity and typicality in matrix distributional semantics
S Ramgoolam, M Sadrzadeh, L Sword – arXiv preprint arXiv:1912.10839, 2019 – arxiv.org
Constructions in type-driven compositional distributional semantics associate large collections of matrices of size $ D $ to linguistic corpora. We develop the proposal of analysing the statistical characteristics of this data in the framework of permutation invariant …

Deploying Semaphores and Distributional Semantics with EyetIUD
E Smith, K Shepherd, R Gordon – International Journal of Software …, 2019 – ssysrm.org
The theoretical unification of multi-processors and Rapid Application Development has analyzed multicast approaches, and current trends suggest that the visualization of active networks will soon emerge\citecite: 0. After years of theoretical research into 32 bit …

Feature2Vec: Distributional semantic modelling of human property knowledge
S Derby, P Miller, B Devereux – arXiv preprint arXiv:1908.11439, 2019 – arxiv.org
Feature norm datasets of human conceptual knowledge, collected in surveys of human volunteers, yield highly interpretable models of word meaning and play an important role in neurolinguistic research on semantic cognition. However, these datasets are limited in size …

Distributional Semantics Meets Multi-Label Learning
V Gupta, R Wadbude, N Natarajan, H Karnick… – Proceedings of the AAAI …, 2019 – aaai.org
We present a label embedding based approach to large-scale multi-label learning, drawing inspiration from ideas rooted in distributional semantics, specifically the Skip Gram Negative Sampling (SGNS) approach, widely used to learn word embeddings. Besides leading to a …

Refining Distributional Semantics Using Event-Driven Epistemologies
C Torres, K Vasquez, M Elliott… – Recent advances in …, 2019 – jrasecs.org
Unified atomic information have led to many compelling advances, including Rapid Application Development and hierarchical databases\citecite: 0. Here, authors demonstrate the visualization of online algorithms. RowRise, our new framework for lossless …

Comparing Distributional Semantics and Distributed Services
S Russell, G McKenna, J Procter – Systems and Software …, 2019 – ssepublication.com
Many theorists would agree that, had it not been for secure modalities, the improvement of virtual machines might never have occurred. Given the trends in metamorphic epistemologies, programmers dubiously note the evaluation of Software Development …

Investigating Antigram Behaviour using Distributional Semantics
S Sengupta – arXiv preprint arXiv:1901.05066, 2019 – arxiv.org
Language is an extremely interesting subject to study, each day presenting new challenges and new topics for research. Words in particular have several unique characteristics which when explored, prove to be astonishing. Anagrams and Antigrams are such words …

Distributional semantics goes to church
M Montes, D Geeraerts… – … , Date: 2019/07/22 …, 2019 – montesmariana.github.io
Page 1. Distributional semantics goes to church Mariana Montes, Dirk Geeraerts, Dirk Speelman, Kris Heylen (QLVL, KU Leuven) How can we use visual analytics to explore the performance of token-level vector space models? A test on 249 occurrences of church from …

Visualizing Web Browsers and Distributional Semantics
B Suarez – Systems and Software Engineering Publication, 2019 – ssepublication.com
Statisticians agree that estimation models are an interesting new topic in the field of software design, and systems engineers concur. In this position paper, authors show the emulation of Web services, which embodies the significant principles of distributed systems. Erminois, our …

Problem Domain Ontology Mining Based on Distributional Semantics
E Kozerenko, Y Sinyaghina, N Somin… – 2019 International …, 2019 – ieeexplore.ieee.org
The paper presents the method of creating an extended ontology as an associative portrait of a subject area and the construction of a semantic space for intelligent knowledge extracting systems development. The ideology of semantic contextual spaces is based on …

A Methodology for the Understanding of Distributional Semantics
N Graham, C Dixon, J Fleming – Systems and Software …, 2019 – ssepublication.com
Unified homogeneous technology have led to many private advances, including rasterization and kernels. Given the current status of client-server communication, developers daringly desire the refinement of online algorithms, which embodies the …

Interactive, Lean Modalities for Distributional Semantics
J Bell, N Evans, L Price – Computer Science and Information Technology …, 2019 – csitpub.org
Performance engineering and decision support systems, while typical in theory, have not until recently been considered compelling. In this work, authors show the construction of e-business. We concentrate our efforts on arguing that the infamous read-write algorithm for …

Decoupling Distributional Semantics from Replication in Markov Models
A Smith, R Henry – Software engineering and CS Journal, 2019 – secsjr.org
Many cyberneticists would agree that, had it not been for the memory bus, the private unification of congestion control and structured programming might never have occurred. In this paper, authors argue the exploration of Distributed scrum, which embodies the …

A Methodology for the Refinement of Distributional Semantics
J Allen, K Pratt, L Smith – Recent advances in software engineering and …, 2019 – jrasecs.org
Redundancy and the location-identity split, while theoretical in theory, have not until recently been considered natural. in our research, authors show the emulation of requirements engineering, which embodies the unfortunate principles of software analysis. Our focus in …

Constructing syntax-based distributional semantic models for novel languages
J Utt – 2019 – elib.uni-stuttgart.de
Computational models of word meaning typically rely on large collections of text data in the language of interest. In the age of ever-increasing numbers of websites the text corpora needed for creating such distributional semantic models (DSMs) that are robust and high …

Token-based distributional semantics and lexical lectometry
S De Pascale, S Marzo… – … , Date: 2019/06/26-2019/06 …, 2019 – lirias.kuleuven.be
Page 1. Token-based distributional semantics and lexical lectometry Stefano De Pascale, Stefania Marzo, Dirk Speelman RU Quantitative Lexicology and Variational Linguistics Page 2. overview 1. lexical lectometry: concepts, workflow and metrics 2. the polysemy issue in lexical lectometry …

Decoupling Write-Back Caches from Distributional Semantics in Courseware
J Martinez, B Bryant, J Weber – Recent advances in software …, 2019 – jrasecs.org
Congestion control and architecture, while robust in theory, have not until recently been considered private. In this work, we disconfirm the construction of digital-to-analog converters, demonstrates the unfortunate importance of software analysis\citecite: 0. In order …

Synthesizing Distributional Semantics Using Lean Information
J Smith – Recent advances in software engineering and …, 2019 – jrasecs.org
The simulation of kernels has synthesized pair programming, and current trends suggest that the evaluation of functional decomposition will soon emerge. In this paper, authors show the deployment of e-commerce, demonstrates the confirmed importance of software design …

TransferLF as Functor in Compositional Distributional Semantics
E Meng – 2019 – academia.edu
The goal of this paper is to systematically construct the TransferLF functor by modeling both the syntactic and the semantic categories as compact closed monoidal categories equipped with a Frobenius algebra. This will be an accessible exposition of the program initiated by …

Mapping Distributional Semantics to Formal Concept Lattice-based Property Norms
D Li, D Summers-Stay – 2019 – easychair.org
Distributional models characterize the meaning of a word by its observed contexts. They have shown great success in many natural language processing tasks, however they are unable to differentiate clearly between different semantic relations. In cognitive psychology …

Mining Labor Market Requirements Using Distributional Semantic Models and Deep Learning
D Botov, J Klenin, A Melnikov, Y Dmitrin… – … Conference on Business …, 2019 – Springer
This article describes a new method for analyzing labor market requirements by matching job listings from online recruitment platforms with professional standards to weigh the importance of particular professional functions and requirements and enrich the general …

Evaluation of Distributional Semantic Models for the Extraction of Semantic Relations for Named Rivers from a Small Specialized Corpus
J Rojas Garcia, P Faber – 2019 – rua.ua.es
EcoLexicon (http://ecolexicon. ugr. es) is a terminological knowledge base on environmental science, whose design permits the geographic contextualization of data. For the geographic contextualization of landform concepts such as named rivers (eg, Nile River), distributional  …

Knowledge-Based Word Sense Disambiguation with Distributional Semantic Expansion
H Rouhizadeh, M Shamsfard… – Proceedings of the 2019 …, 2019 – aclweb.org
Creative Commons License ACL materials are Copyright © 1963–2019 ACL; other materials are copyrighted by their respective copyright holders. Materials prior to 2016 here are licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 International …

Noun Compositionality Detection Using Distributional Semantics for the Russian Language
D Puzyrev, A Shelmanov, A Panchenko… – … Conference on Analysis …, 2019 – Springer
In this paper, we present the first gold-standard corpus of Russian noun compounds annotated with compositionality information. We used Universal Dependency treebanks to collect noun compounds according to part of speech patterns, such as ADJ-NOUN or NOUN …

Using the Outlier Detection Task to Evaluate Distributional Semantic Models
P Gamallo – Machine Learning and Knowledge Extraction, 2019 – mdpi.com
In this article, we define the outlier detection task and use it to compare neural-based word embeddings with transparent count-based distributional representations. Using the English Wikipedia as a text source to train the models, we observed that embeddings outperform …

Towards the Automatic Construction of a Multilingual Dictionary of Collocations using Distributional Semantics
M Garcia, M García-Salido… – Electronic lexicography in …, 2019 – grupolys.org
This paper presents the method used to create a multilingual online dictionary of collocations of English, Portuguese, and Spanish. This resource is built automatically and contains three types of collocations: verb–object (eg,“[to] issue [an] invoice”), adjective–noun …

Re-Representing Metaphor: Modelling metaphor perception using dynamically contextual distributional semantics
S McGregor, K Agres, K Rataj, M Purver… – Frontiers in …, 2019 – frontiersin.org
In this paper, we present a novel context-dependent approach to modelling word meaning, and apply it to the modelling of metaphor. In distributional semantic approaches, words are represented as points in a high dimensional space generated from co-occurrence statistics; …

Mapping Distributional Semantics to Property Norms with Deep Neural Networks
D Li, D Summers-Stay – Big Data and Cognitive Computing, 2019 – mdpi.com
Word embeddings have been very successful in many natural language processing tasks, but they characterize the meaning of a word/concept by uninterpretable “context signatures”. Such a representation can render results obtained using embeddings difficult to interpret …

Word sense induction in bengali using parallel corpora and distributional semantics
S Sengupta, R Pandit, P Mitra… – Journal of Intelligent …, 2019 – content.iospress.com
One of the most challenging research problems in natural language processing (NLP) is that of word sense induction (WSI). It involves discovering senses of a word given its contexts of usage without the use of a sense inventory which differentiates it from traditional word sense …

Decoupling Distributional Semantics from Thin Clients in Neural Networks
K McFarlane – International Journal of Software Systems Research …, 2019 – ssysrm.org
Many information theorists would agree that, had it not been for highly-available epistemologies, the deployment of Lean software development might never have occurred\citecite: 0. In fact, few software engineers would disagree with the private …

Distributional semantics in the real world: building word vector representations from a truth-theoretic model
E Kuzmenko, A Herbelot – … of the 13th International Conference on …, 2019 – aclweb.org
Distributional semantics models (DSMs) are known to produce excellent representations of word meaning, which correlate with a range of behavioural data. As lexical representations, they have been said to be fundamentally different from truth-theoretic models of semantics …

Towards Interpretable, Data-derived Distributional Semantic Representations for Reasoning: A Dataset of Properties and Concepts
P Sommerauer, A Fokkens, P Vossen – Wordnet Conference, 2019 – academia.edu
This paper proposes a framework for investigating which types of semantic properties are represented by distributional data. The core of our framework consists of relations between concepts and properties. We provide hypotheses on which properties are reflected in …

Distributional, semantic and functional properties of adversative pragmatic markers in Italian: A corpus-based approach
D Cimmino – BOOK OF ABSTRACTS – sle2019.eu
Pragmatic markers can perform textual and dialogic functions: ie they can link portions of texts (utterances, paragraphs, etc.) as well as guide the interaction with the addressee. The complete description of their uses is still debated (see Degand et al. 2013; Fedriani/Sansò …

Why So Down? The Role of Negative (and Positive) Pointwise Mutual Information in Distributional Semantics
A Salle, A Villavicencio – arXiv preprint arXiv:1908.06941, 2019 – arxiv.org
In distributional semantics, the pointwise mutual information ($\mathit {PMI} $) weighting of the cooccurrence matrix performs far better than raw counts. There is, however, an issue with unobserved pair cooccurrences as $\mathit {PMI} $ goes to negative infinity. This …

Distributional Semantics Meets Construction Grammar. Towards a Unified Usage-Based Model of Grammar and Meaning
G Rambelli, E Chersoni, P Blache, CR Huang, A Lenci – 2019 – hal.archives-ouvertes.fr
In this paper, we propose a new type of semantic representation of Construction Grammar that combines constructions with the vector representations used in Distributional Semantics. We introduce a new framework, Distribu-tional Construction Grammar, where …

Conceptual Change and Distributional Semantic Models: an Exploratory Study on Pitfalls and Possibilities
P Sommerauer, A Fokkens – … of the 1st International Workshop on …, 2019 – aclweb.org
Studying conceptual change using embedding models has become increasingly popular in the Digital Humanities community while critical observations about them have received less attention. This paper investigates what the impact of known pitfalls can be on the …

Distributional, semantic and functional properties of adversative pragmatic markers in Italian: A corpus-based approach
J Chojnicka, ?P Paku?a – BOOK OF ABSTRACTS – lirias.kuleuven.be
Pragmatic markers can perform textual and dialogic functions: ie they can link portions of texts (utterances, paragraphs, etc.) as well as guide the interaction with the addressee. The complete description of their uses is still debated (see Degand et al. 2013; Fedriani/Sansò …

Can prediction-based distributional semantic models predict typicality?
T Heyman, G Heyman – Quarterly Journal of Experimental …, 2019 – journals.sagepub.com
Recent advances in the field of computational linguistics have led to the development of various prediction-based models of semantics. These models seek to infer word representations from large text collections by predicting target words from neighbouring …

Combatting The Challenges of Local Privacy for Distributional Semantics with Compression
A Schofield, G Yauney, D Mimno – priml-workshop.github.io
Traditional methods for adding locally private noise to bag-of-words features overwhelm the true signal in the text data, removing the properties of sparsity and non-negativity often relied upon by distributional semantic models. We argue the formulation of limited-precision local …

Paintball–Automated Wordnet Expansion Algorithm based on Distributional Semantics and Information Spreading
M Piasecki – Computational Methods in Science and …, 2019 – pdfs.semanticscholar.org
plWordNet has been consequently built on the basis of the corpus-based wordnet development method. As plWordNet construction had started from scratch it was necessary to find a way to reduce the amount of work required, and not to reduce the quality. In the …

What do you mean, BERT? Assessing BERT as a Distributional Semantics Model
T Mickus, D Paperno, M Constant… – arXiv preprint arXiv …, 2019 – arxiv.org
Contextualized word embeddings, ie vector representations for words in context, are naturally seen as an extension of previous noncontextual distributional semantic models. In this work, we focus on BERT, a deep neural network that produces contextualized …

Detection and Aptness: A study in metaphor detection and aptness assessment through neural networks and distributional semantic spaces
Y Bizzoni – 2019 – gupea.ub.gu.se
Metaphor is one of the most prominent, and most studied, figures of speech. While it is considered an element of great interest in several branches of linguistics, such as semantics, pragmatics and stylistics, its automatic processing remains an open challenge …

Creation and Evaluation of Datasets for Distributional Semantics Tasks in the Digital Humanities Domain
G Wohlgenannt, A Barinova, D Ilvovsky… – arXiv preprint arXiv …, 2019 – arxiv.org
Word embeddings are already well studied in the general domain, usually trained on large text corpora, and have been evaluated for example on word similarity and analogy tasks, but also as an input to downstream NLP processes. In contrast, in this work we explore the …

Distributional semantics and the conceptual foundations of verb meaning: how neural word embeddings memorize the unaccusative hypothesis
T Pross – cssp.cnrs.fr
In the present paper, I investigate whether and how neural word embeddings can be understood to encode not only idiosyncratic aspects of word meaning but also the kind of general and abstract concepts that are central to theoretical approaches of lexical …

Bad Form: Comparing Context-Based and Form-Based Few-Shot Learning in Distributional Semantic Models
J Van Hautte, G Emerson, M Rei – arXiv preprint arXiv:1910.00275, 2019 – arxiv.org
Word embeddings are an essential component in a wide range of natural language processing applications. However, distributional semantic models are known to struggle when only a small number of context sentences are available. Several methods have been …

Using online update of distributional semantics models for decision-making support for concepts extraction in the domain ontology learning task
A Anikin, A Katyshev, M Denisov… – IOP Conference …, 2019 – iopscience.iop.org
Most of the information processed by computer systems is presented in the form of text corpuses. The number of such texts (as well as the corpus as a whole) only increases with time, and therefore the word processing tasks remain relevant to this day. Ontology allows to …

Reply to Lewis et al.: Inference is key to learning appearance from language, for humans and distributional semantic models alike
JS Kim, GV Elli, M Bedny – Proceedings of the National …, 2019 – National Acad Sciences
Two major ways in which humans learn is by direct sensory observation and gathering information from other minds through language. In our original paper, we attempt to tease apart the contributions of sensory experience from other sources of information, including …

A comprehensive analysis of the parameters in the creation and comparison of feature vectors in distributional semantic models for multiple languages
A Dobó – 2019 – doktori.bibl.u-szeged.hu
Measuring the semantic similarity and relatedness of words is important for many natural language processing tasks. Although distributional semantic models designed for this task have many different parameters, such as vector similarity measures, weighting schemes and …

Evaluating distributional representations of verb semantic selection
E Jezek, EM Ponti, B Magnini – Workshop on Interoperable Semantic …, 2019 – sigsem.uvt.nl
… semantic selection. To achieve this purpose, we extract the word vectors corresponding to our lexical set vocabulary from the word2vec distributional semantic model, and then perform k-means clustering on these. We focus …

A Distributional Model of Affordances in Semantic Type Coercion
S McGregor, E Jezek – Proceedings of the 13th International Conference …, 2019 – aclweb.org
… Motivated by an analysis of some of the shortcomings of a more general probabilistic approach, and also by a number of pre- vious approaches to interpreting semantic coercion, we outline a model grounded in the distributional semantic modelling paradigm (Clark, 2015) …

Semantic Relata for the Evaluation of Distributional Models in Mandarin Chinese
H Liu, E Chersoni, N Klyueva, E Santus… – IEEE Access, 2019 – ieeexplore.ieee.org
… 11070079614059 and Grant 10000086393101. ABSTRACT Distributional Semantic Models (DSMs) established themselves as a standard for the represen- tation of word and sentence meaning. However, DSMs provide quantitative …

Contextualized Translations of Phrasal Verbs with Distributional Compositional Semantics and Monolingual Corpora
P Gamallo, S Sotelo, JR Pichel, M Artetxe – Computational Linguistics, 2019 – MIT Press
… Compositional models in distributional semantics combine word vectors to yield new compositional vectors that represent the meaning of composite expressions. Some compositional approaches use syntactically enriched vector …

Leveraging Distributional and Relational Semantics for Knowledge Extraction from Textual Corpora
G ROSSIELLO, G SEMERARO, M DI CIANO – 2019 – researchgate.net
… In detail, we exploit both distributional semantics models and struc- tured relational data sources, and their combination, in order to learn representa- tions which help existing models when they work with few or in absence of training data …

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