[PDF] Modelling With Words eBook

Author : Jonathan Lawry
Publisher : Springer Science & Business Media
Page : 241 pages
File Size : 21,74 MB
Release : 2003-11-10
Category : Computers
ISBN : 3540204873

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Modelling with Words is an emerging modelling methodology closely related to the paradigm of Computing with Words introduced by Lotfi Zadeh. This book is an authoritative collection of key contributions to the new concept of Modelling with Words. A wide range of issues in systems modelling and analysis is presented, extending from conceptual graphs and fuzzy quantifiers to humanist computing and self-organizing maps. Among the core issues investigated are - balancing predictive accuracy and high level transparency in learning - scaling linguistic algorithms to high-dimensional data problems - integrating linguistic expert knowledge with knowledge derived from data - identifying sound and useful inference rules - integrating fuzzy and probabilistic uncertainty in data modelling

Author : Julia Silge
Publisher : "O'Reilly Media, Inc."
Page : 193 pages
File Size : 42,63 MB
Release : 2017-06-12
Category : Computers
ISBN : 1491981628

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Chapter 7. Case Study : Comparing Twitter Archives; Getting the Data and Distribution of Tweets; Word Frequencies; Comparing Word Usage; Changes in Word Use; Favorites and Retweets; Summary; Chapter 8. Case Study : Mining NASA Metadata; How Data Is Organized at NASA; Wrangling and Tidying the Data; Some Initial Simple Exploration; Word Co-ocurrences and Correlations; Networks of Description and Title Words; Networks of Keywords; Calculating tf-idf for the Description Fields; What Is tf-idf for the Description Field Words?; Connecting Description Fields to Keywords; Topic Modeling.

Author : Gogate, Lakshmi
Publisher : IGI Global
Page : 451 pages
File Size : 43,57 MB
Release : 2013-02-28
Category : Computers
ISBN : 1466629746

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The process of learning words and languages may seem like an instinctual trait, inherent to nearly all humans from a young age. However, a vast range of complex research and information exists in detailing the complexities of the process of word learning. Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence strives to combine cross-disciplinary research into one comprehensive volume to help readers gain a fuller understanding of the developmental processes and influences that makeup the progression of word learning. Blending together developmental psychology and artificial intelligence, this publication is intended for researchers, practitioners, and educators who are interested in language learning and its development as well as computational models formed from these specific areas of research.

Author : Jason Brownlee
Publisher : Machine Learning Mastery
Page : 413 pages
File Size : 31,6 MB
Release : 2017-11-21
Category : Computers
ISBN :

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Deep learning methods are achieving state-of-the-art results on challenging machine learning problems such as describing photos and translating text from one language to another. In this new laser-focused Ebook, finally cut through the math, research papers and patchwork descriptions about natural language processing. Using clear explanations, standard Python libraries and step-by-step tutorial lessons you will discover what natural language processing is, the promise of deep learning in the field, how to clean and prepare text data for modeling, and how to develop deep learning models for your own natural language processing projects.

Author : Marianna Bolognesi
Publisher : John Benjamins Publishing Company
Page : 222 pages
File Size : 37,86 MB
Release : 2020-11-15
Category : Language Arts & Disciplines
ISBN : 9027260427

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Words are not just labels for conceptual categories. Words construct conceptual categories, frame situations and influence behavior. Where do they get their meaning? This book describes how words acquire their meaning. The author argues that mechanisms based on associations, pattern detection, and feature matching processes explain how words acquire their meaning from experience and from language alike. Such mechanisms are summarized by the distributional hypothesis, a computational theory of meaning originally applied to word occurrences only, and hereby extended to extra-linguistic contexts. By arguing in favor of the cognitive foundations of the distributional hypothesis, which suggests that words that appear in similar contexts have similar meaning, this book offers a theoretical account for word meaning construction and extension in first and second language that bridges empirical findings from cognitive and computer sciences. Plain language and illustrations accompany the text, making this book accessible to a multidisciplinary academic audience.

Author : S., Sumathi
Publisher : IGI Global
Page : 227 pages
File Size : 36,12 MB
Release : 2019-11-29
Category : Computers
ISBN : 1799811611

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Information in today’s advancing world is rapidly expanding and becoming widely available. This eruption of data has made handling it a daunting and time-consuming task. Natural language processing (NLP) is a method that applies linguistics and algorithms to large amounts of this data to make it more valuable. NLP improves the interaction between humans and computers, yet there remains a lack of research that focuses on the practical implementations of this trending approach. Neural Networks for Natural Language Processing is a collection of innovative research on the methods and applications of linguistic information processing and its computational properties. This publication will support readers with performing sentence classification and language generation using neural networks, apply deep learning models to solve machine translation and conversation problems, and apply deep structured semantic models on information retrieval and natural language applications. While highlighting topics including deep learning, query entity recognition, and information retrieval, this book is ideally designed for research and development professionals, IT specialists, industrialists, technology developers, data analysts, data scientists, academics, researchers, and students seeking current research on the fundamental concepts and techniques of natural language processing.

Author : Gert Westermann
Publisher : Routledge
Page : 300 pages
File Size : 37,34 MB
Release : 2017-11-10
Category : Psychology
ISBN : 1317550587

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Early Word Learning explores the processes leading to a young child learning words and their meanings. Word learning is here understood as the outcome of overlapping and interacting processes, starting with an infant’s learning of native speech sounds to segmenting proto-words from fluent speech, mapping individual words to meanings in the face of natural variability and uncertainty, and developing a structured mental lexicon. Experts in the field review the development of early lexical acquisition from empirical, computational and theoretical perspectives to examine the development of skilled word learning as the outcome of a process that begins even before birth and spans the first two years of life. Drawing on cutting-edge research in infant eye-tracking, neuroimaging techniques and computational modelling, this book surveys the field covering both established results and the most recent advances in word learning research. Featuring chapters from international experts whose research approaches the topic from these diverse perspectives using different methodologies, this book provides a comprehensive yet coherent and unified representation of early word learning. It will be invaluable for both undergraduate and postgraduate courses in early language development as well as being of interest to researchers interested in lexical development.

Author : Jonathan Lawry
Publisher : Springer
Page : 241 pages
File Size : 33,12 MB
Release : 2003-10-28
Category : Computers
ISBN : 3540399062

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Modelling with Words is an emerging modelling methodology closely related to the paradigm of Computing with Words introduced by Lotfi Zadeh. This book is an authoritative collection of key contributions to the new concept of Modelling with Words. A wide range of issues in systems modelling and analysis is presented, extending from conceptual graphs and fuzzy quantifiers to humanist computing and self-organizing maps. Among the core issues investigated are - balancing predictive accuracy and high level transparency in learning - scaling linguistic algorithms to high-dimensional data problems - integrating linguistic expert knowledge with knowledge derived from data - identifying sound and useful inference rules - integrating fuzzy and probabilistic uncertainty in data modelling

Author : Emily Calhoun
Publisher : ASCD
Page : 134 pages
File Size : 13,45 MB
Release : 1999
Category : Education
ISBN : 0871203375

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In this practical guide to teaching beginning language learners of all ages, Calhoun encourages us to begin where the learners begin--with their developed listening and speaking vocabularies and other accumulated knowledge about the world. Engage students in shaking words out of a picture--words from their speaking vocabularies--to begin the process of building their reading and writing skills. Use the picture word inductive model (PWIM) to teach several skills simultaneously, beginning with the mechanics of forming letters to hearing and identifying the phonetic components of language, to classifying words and sentences, through forming paragraphs and stories based on observation. Built into the PWIM is the structure required to assess the needs and understandings of your students immediately, adjust the lesson in response, and to use explicit instruction and inductive activities. Individual, small-group, and large-group activities are inherent to the model and flow naturally as the teacher arranges instruction according to the 10 steps of the PWIM. Students and teachers move through the model and work on developing skills and abilities in reading, writing, listening, and comprehension as tools for thinking, learning, and sharing ideas.