Distributional Semantics

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Distributional Semantics

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Author : Alessandro Lenci
language : en
Publisher: Cambridge University Press
Release Date : 2023-09-21

Distributional Semantics written by Alessandro Lenci and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-21 with Computers categories.

This book provides a comprehensive foundation of distributional methods in computational modeling of meaning. It aims to build a common understanding of the theoretical and methodological foundations for students of computational linguistics, natural language processing, computer science, artificial intelligence, and cognitive science.

Word Knowledge And Word Usage

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Author : Vito Pirrelli
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2020-04-20

Word Knowledge And Word Usage written by Vito Pirrelli and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-20 with Language Arts & Disciplines categories.

Word storage and processing define a multi-factorial domain of scientific inquiry whose thorough investigation goes well beyond the boundaries of traditional disciplinary taxonomies, to require synergic integration of a wide range of methods, techniques and empirical and experimental findings. The present book intends to approach a few central issues concerning the organization, structure and functioning of the Mental Lexicon, by asking domain experts to look at common, central topics from complementary standpoints, and discuss the advantages of developing converging perspectives. The book will explore the connections between computational and algorithmic models of the mental lexicon, word frequency distributions and information theoretical measures of word families, statistical correlations across psycho-linguistic and cognitive evidence, principles of machine learning and integrative brain models of word storage and processing. Main goal of the book will be to map out the landscape of future research in this area, to foster the development of interdisciplinary curricula and help single-domain specialists understand and address issues and questions as they are raised in other disciplines.

Rivista Di Linguistica

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Author :
language : en
Publisher:
Release Date : 2007

Rivista Di Linguistica written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Linguistics categories.

Similarity Models In Distributional Semantics Using Task Specific Information

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Author : Rosa Tsegaye Aga
language : en
Publisher:
Release Date : 2019

Similarity Models In Distributional Semantics Using Task Specific Information written by Rosa Tsegaye Aga and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

Towards Unifying Grounded And Distributional Semantics Using The Words As Classifiers Model Of Lexical Semantics

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Author : Stacy Black
language : en
Publisher:
Release Date : 2020

Towards Unifying Grounded And Distributional Semantics Using The Words As Classifiers Model Of Lexical Semantics written by Stacy Black and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computational linguistics categories.

"Automated systems that make use of language, such as personal assistants, need some means of representing words such that 1) the representation is computable and 2) captures form and meaning. Recent advancements in the field of natural language processing have resulted in useful approaches to representing computable word meanings. In this thesis, I consider two such approaches: distributional embeddings and grounded models. Distributional embeddings are represented as high-dimensional vectors; words with similar meanings tend to cluster together in embedding space. Embeddings are easily learned using large amounts of text data. However, embeddings suffer from a lack of "real world" knowledge; for example, the knowledge of identifying colors or objects as they appear. In contrast to embeddings, grounded models learn a mapping between language and the physical world, such as visual information in pictures. Grounded models, however, tend to focus only on the mapping between language and the physical world and lack the knowledge that could be gained from considering abstract information found in text. In this thesis, I evaluate wac2vec, a model that brings together grounded and distributional semantics to work towards leveraging the relative strengths of both, and use empirical analysis to explore whether wac2vec adds semantic information to traditional embeddings. Starting with the words-as-classifiers (WAC) model of grounded semantics, I use a large repository of images and the keywords that were used to retrieve those images. From the grounded model, I extract classifier coefficients as word-level vector embeddings (hence, wac2vec), then combine those with embeddings from distributional word representations. I show that combining grounded embeddings with traditional embeddings results in improved performance in a visual task, demonstrating the viability of using the wac2vec model to enrich traditional embeddings, and showing that wac2vec provides important semantic information that these embeddings do not have on their own."--Boise State University ScholarWorks.

Tenth International Workshop On Database And Expert Systems Applications

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Author : Antonio Cammelli
language : en
Publisher: Institute of Electrical & Electronics Engineers(IEEE)
Release Date : 1999

Tenth International Workshop On Database And Expert Systems Applications written by Antonio Cammelli and has been published by Institute of Electrical & Electronics Engineers(IEEE) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with Computers categories.

Proceedings of the September 1999 workshop on defining requirements for future systems in the areas of database and artificial technologies. The 151 contributions discuss innovative applications and new architectures; mobility in databases and distributed systems; similarity search; web-based inform"

Research Memorandum

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Author : Rand Corporation
language : en
Publisher:
Release Date : 1963

Research Memorandum written by Rand Corporation and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1963 with Research categories.

Data Science Classification And Related Methods

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Author : International Federation of Classification Societies. Conference
language : en
Publisher: Springer
Release Date : 1998-03

Data Science Classification And Related Methods written by International Federation of Classification Societies. Conference and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-03 with Business & Economics categories.

This volume contains selected papers covering a wide range of topics, including theoretical and methodological advances relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge seeking and discovery. The result is a broad view of the state of the art, making this an essential work not only for data analysts, mathematicians, and statisticians, but also for researchers involved in data processing at all stages from data gathering to decision making.

Exploring Distributional Semantics In Lexical Representations And Narrative Modeling

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Author : Su Wang
language : en
Publisher:
Release Date : 2020

Exploring Distributional Semantics In Lexical Representations And Narrative Modeling written by Su Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

We are interested in the computational modeling of lexico-conceptual and narrative knowledge (e.g. how to represent the meaning of cat to reflect facts such as: it is similar to a dog, and it is typically larger than a mouse; how to characterize story, and how to identify different narratives on the same topic). On the lexico-conceptual front, we learn lexical representations with strong interpretability, as well as integrate commonsense knowledge into lexical representations. For narrative modeling, we study how to identify, extract, and generate narratives/stories acceptable to human intuition. As a methodological framework we apply the methods of Distributional Semantics (DS) — “a subfield of Natural Language Processing that learns meaning from word usages” (Herbelot, 2019) — where semantic representations (on any levels such as word, phrases, sentences, etc.) are learned at scale from data through machine learning models (Erk and Padó, 2008; Baroni and Lenci, 2010; Mikolov et al., 2013; Pennington et al., 2014). To infuse interpretability and commonsense into semantic representations (specifically lexical and event), which are typically lacking in previous works (Doran et al., 2017; Gusmao et al., 2018; Carvalho et al., 2019), we complement the data-driven scalability with a minimal amount of human knowledge annotation on a selected set of tasks and have obtained empirical evidence in support of our techniques. For narrative modeling, we draw insights from the rich body of work on scripts and narratives started from Schank and Abelson (1977) and Mooney and DeJong (1985) to Chambers and Jurafsky (2008, 2009), and proposed distributional models for the tasks narrative identification, extraction, and generation which produced state-of-the-art performance. Symbolic approaches to lexical semantics (Wierzbicka, 1996; Goddard and Wierzbicka, 2002) and narrative modeling (Schank and Abelson, 1977; Mooney and DeJong, 1985) have been fruitful on the front of theoretical studies. For example, in theoretical linguistics, Wierzbicka defined a small set of lexical semantic primitives from which complex meaning can be built compositionally; in Artificial Intelligence, Schank and Abelson formulated primitive acts which are conceptualized into semantic episodes (i.e. scripts) understandable by humans. Our focus, however, is primarily on computational approaches that need wide lexical coverage, for which DS provides a better toolkit, especially in practical applications. In this thesis, we innovate by building on the “vanilla” DS techniques (Landauer and Dumais, 1997; Mikolov et al., 2013) to address the issues listed above. Specifically, we present empirical evidence that • On the building block level, with the framework of DS, it is possible to learn highly interpretable lexical and event representations at scale and introduce human commonsense knowledge at low cost. • On the narrative level, well-designed DS modeling offers a balance of precision and scalability, solutions which are empirically stronger to complex narrative modeling questions (e.g. narrative identification, extraction and generation). Further, conducting case-studies on lexical and narrative modeling, we showcase the viability of integrating DS with traditional methods in complementation to retain the strengths of both approaches Concretely, the contributions of this thesis are summarized as follows: • Evidence from analyzing/modeling a small set of common concepts which indicates that interpretable representations can be learned for lexical concepts with minimal human annotation to realize one/few-shot learning. • Commonsense integration in lexical semantics: with carefully designed crowdsourcing, and combined with distributional methods, it is possible to substantially improve inference related to physical knowledge of the world. • Neural distributional methods perform strongly in complex narrative modeling tasks, where we demonstrate that the following techniques are particularly useful: 1) human intuition inspired iterative algorithms; 2) integration of graphical and distributional modeling; pre-trained large-scale language models

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Author :
language : en
Publisher:
Release Date : 2014

written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Chinese language categories.