Download or read book Modelling with Words written by Jonathan Lawry and published by Springer Science & Business Media. This book was released on 2003-11-10 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Text Mining with R written by Julia Silge and published by "O'Reilly Media, Inc.". This book was released on 2017-06-12 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Theoretical and Computational Models of Word Learning Trends in Psychology and Artificial Intelligence written by Gogate, Lakshmi and published by IGI Global. This book was released on 2013-02-28 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Where Words Get their Meaning written by Marianna Bolognesi and published by John Benjamins Publishing Company. This book was released on 2020-11-15 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Deep Learning for Natural Language Processing written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2017-11-21 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Applications of Topic Models written by Jordan Boyd-Graber and published by Now Publishers. This book was released on 2017-07-13 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes recent academic and industrial applications of topic models with the goal of launching a young researcher capable of building their own applications of topic models.
Download or read book Neural Networks for Natural Language Processing written by S., Sumathi and published by IGI Global. This book was released on 2019-11-29 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Teaching Beginning Reading and Writing with the Picture Word Inductive Model written by Emily Calhoun and published by ASCD. This book was released on 1999 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book The Na ve Bayes Model for Unsupervised Word Sense Disambiguation written by Florentina T. Hristea and published by Springer Science & Business Media. This book was released on 2012-11-07 with total page 79 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances (from 2008 to 2012) concerning use of the Naïve Bayes model in unsupervised word sense disambiguation (WSD). While WSD, in general, has a number of important applications in various fields of artificial intelligence (information retrieval, text processing, machine translation, message understanding, man-machine communication etc.), unsupervised WSD is considered important because it is language-independent and does not require previously annotated corpora. The Naïve Bayes model has been widely used in supervised WSD, but its use in unsupervised WSD has led to more modest disambiguation results and has been less frequent. It seems that the potential of this statistical model with respect to unsupervised WSD continues to remain insufficiently explored. The present book contends that the Naïve Bayes model needs to be fed knowledge in order to perform well as a clustering technique for unsupervised WSD and examines three entirely different sources of such knowledge for feature selection: WordNet, dependency relations and web N-grams. WSD with an underlying Naïve Bayes model is ultimately positioned on the border between unsupervised and knowledge-based techniques. The benefits of feeding knowledge (of various natures) to a knowledge-lean algorithm for unsupervised WSD that uses the Naïve Bayes model as clustering technique are clearly highlighted. The discussion shows that the Naïve Bayes model still holds promise for the open problem of unsupervised WSD.
Download or read book DNA Words and Models written by Stéphane Robin and published by Cambridge University Press. This book was released on 2005-10-13 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher Description
Download or read book Mastering Machine Learning with Spark 2 x written by Alex Tellez and published by Packt Publishing Ltd. This book was released on 2017-08-31 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the complexities of machine learning algorithms in Spark to generate useful data insights through this data analysis tutorial About This Book Process and analyze big data in a distributed and scalable way Write sophisticated Spark pipelines that incorporate elaborate extraction Build and use regression models to predict flight delays Who This Book Is For Are you a developer with a background in machine learning and statistics who is feeling limited by the current slow and “small data” machine learning tools? Then this is the book for you! In this book, you will create scalable machine learning applications to power a modern data-driven business using Spark. We assume that you already know the machine learning concepts and algorithms and have Spark up and running (whether on a cluster or locally) and have a basic knowledge of the various libraries contained in Spark. What You Will Learn Use Spark streams to cluster tweets online Run the PageRank algorithm to compute user influence Perform complex manipulation of DataFrames using Spark Define Spark pipelines to compose individual data transformations Utilize generated models for off-line/on-line prediction Transfer the learning from an ensemble to a simpler Neural Network Understand basic graph properties and important graph operations Use GraphFrames, an extension of DataFrames to graphs, to study graphs using an elegant query language Use K-means algorithm to cluster movie reviews dataset In Detail The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment. Style and approach This book takes a practical approach to help you get to grips with using Spark for analytics and to implement machine learning algorithms. We'll teach you about advanced applications of machine learning through illustrative examples. These examples will equip you to harness the potential of machine learning, through Spark, in a variety of enterprise-grade systems.
Download or read book Teaching Beginning Reading and Writing with the Picture Word Inductive Model written by Emily F. Calhoun and published by ASCD. This book was released on 1999-03-15 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Note: This product listing is for the Adobe Acrobat (PDF) version of the book.
Download or read book Supervised Machine Learning for Text Analysis in R written by Emil Hvitfeldt and published by CRC Press. This book was released on 2021-10-22 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.
Download or read book The Structure of the Lexicon written by Jürgen Handke and published by Walter de Gruyter. This book was released on 2012-08-06 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Computer Vision ACCV 2012 Workshops written by Jong-Il Park and published by Springer. This book was released on 2013-03-27 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two volume set, consisting of LNCS 7728 and 7729, contains the carefully reviewed and selected papers presented at the nine workshops that were held in conjunction with the 11th Asian Conference on Computer Vision, ACCV 2012, in Daejeon, South Korea, in November 2012. From a total of 310 papers submitted, 78 were selected for presentation. LNCS 7728 contains the papers selected for the International Workshop on Computer Vision with Local Binary Pattern Variants, the Workshop on Computational Photography and Low-Level Vision, the Workshop on Developer-Centered Computer Vision, and the Workshop on Background Models Challenge. LNCS 7729 contains the papers selected for the Workshop on e-Heritage, the Workshop on Color Depth Fusion in Computer Vision, the Workshop on Face Analysis, the Workshop on Detection and Tracking in Challenging Environments, and the International Workshop on Intelligent Mobile Vision.
Download or read book The Child and Childhood in Folk Thought written by Alexander Francis Chamberlain and published by New York ; London : Macmillan. This book was released on 1895 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
