Natural Language Processing With Java And Lingpipe Cookbook
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Natural Language Processing With Java And Lingpipe Cookbook
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Author : Breck Baldwin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-11-28
Natural Language Processing With Java And Lingpipe Cookbook written by Breck Baldwin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-28 with Computers categories.
This book is for experienced Java developers with NLP needs, whether academics, industrialists, or hobbyists. A basic knowledge of NLP terminology will be beneficial.
Natural Language Processing With Java
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Author : Richard M Reese
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-03-27
Natural Language Processing With Java written by Richard M Reese and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-27 with Computers categories.
If you are a Java programmer who wants to learn about the fundamental tasks underlying natural language processing, this book is for you. You will be able to identify and use NLP tasks for many common problems, and integrate them in your applications to solve more difficult problems. Readers should be familiar/experienced with Java software development.
Natural Language Processing With Java Cookbook
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Author : Richard M. Reese
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-04-25
Natural Language Processing With Java Cookbook written by Richard M. Reese and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-25 with Computers categories.
A problem-solution guide to encounter various NLP tasks utilizing Java open source libraries and cloud-based solutions Key FeaturesPerform simple-to-complex NLP text processing tasks using modern Java libraries Extract relationships between different text complexities using a problem-solution approach Utilize cloud-based APIs to perform machine translation operationsBook Description Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon’s AWS. You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentences, or semantic words. What you will learnExplore how to use tokenizers in NLP processing Implement NLP techniques in machine learning and deep learning applications Identify sentences within the text and learn how to train specialized NER models Learn how to classify documents and perform sentiment analysis Find semantic similarities between text elements and extract text from a variety of sources Preprocess text from a variety of data sources Learn how to identify and translate languagesWho this book is for This book is for data scientists, NLP engineers, and machine learning developers who want to perform their work on linguistic applications faster with the use of popular libraries on JVM machines. This book will help you build real-world NLP applications using a recipe-based approach. Prior knowledge of Natural Language Processing basics and Java programming is expected.
Natural Language Processing With Java And Lingpipe Cookbook
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Author : Breck Baldwin
language : en
Publisher: Packt Publishing
Release Date : 2014-11-28
Natural Language Processing With Java And Lingpipe Cookbook written by Breck Baldwin and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-28 with Computers categories.
This book is for experienced Java developers with NLP needs, whether academics, industrialists, or hobbyists. A basic knowledge of NLP terminology will be beneficial.
Advancing Uncertain Combinatorics Through Graphization Hyperization And Uncertainization Fuzzy Neutrosophic Soft Rough And Beyond
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Author : Takaaki Fujita
language : en
Publisher: Infinite Study
Release Date : 2025-01-20
Advancing Uncertain Combinatorics Through Graphization Hyperization And Uncertainization Fuzzy Neutrosophic Soft Rough And Beyond written by Takaaki Fujita and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-20 with Mathematics categories.
This book is the fifth volume in the series of Collected Papers on Advancing Uncertain Combinatorics through Graphization, Hyperization, and Uncertainization: Fuzzy, Neutrosophic, Soft, Rough, and Beyond. This volume specifically delves into the concept of Various SuperHyperConcepts, building on the foundational advancements introduced in previous volumes. The series aims to explore the ongoing evolution of uncertain combinatorics through innovative methodologies such as graphization, hyperization, and uncertainization. These approaches integrate and extend core concepts from fuzzy, neutrosophic, soft, and rough set theories, providing robust frameworks to model and analyze the inherent complexity of real-world uncertainties. At the heart of this series lies combinatorics and set theory—cornerstones of mathematics that address the study of counting, arrangements, and the relationships between collections under defined rules. Traditionally, combinatorics has excelled in solving problems involving uncertainty, while advancements in set theory have expanded its scope to include powerful constructs like fuzzy and neutrosophic sets. These advanced sets bring new dimensions to uncertainty modeling by capturing not just binary truth but also indeterminacy and falsity. In this fifth volume, the exploration of Various SuperHyperConcepts provides an innovative lens to address uncertainty, complexity, and hierarchical relationships. It synthesizes key methodologies introduced in earlier volumes, such as hyperization and neutrosophic extensions, while advancing new theories and applications. From pioneering hyperstructures to applications in advanced decision-making, language modeling, and neural networks, this book represents a significant leap forward in uncertain combinatorics and its practical implications across disciplines. The book is structured into 17 chapters, each contributing unique perspectives and advancements in the realm of Various SuperHyperConcepts and their related frameworks: Chapter 1 introduces the concept of Body-Mind-Soul-Spirit Fluidity within psychology and phenomenology, while examining established social science frameworks like PDCA and DMAIC. It extends these frameworks using Neutrosophic Sets, a flexible extension of Fuzzy Sets, to improve their adaptability for mathematical and programming applications. The chapter emphasizes the potential of Neutrosophic theory to address multi-dimensional challenges in social sciences. Chapter 2 delves into the theoretical foundation of Hyperfunctions and their generalizations, such as Hyperrandomness and Hyperdecision-Making. It explores higher-order frameworks like Weak Hyperstructures, Hypergraphs, and Cognitive Hypermaps, aiming to establish their versatility in addressing multi-layered problems and setting a foundation for further studies. Chapter 3 extends traditional decision-making methodologies into HyperDecision-Making and n-SuperHyperDecision-Making. By building on approaches like MCDM and TOPSIS, this chapter develops frameworks capable of addressing complex decision-making scenarios, emphasizing their applicability in dynamic, multi-objective contexts. Chapter 4 explores integrating uncertainty frameworks, including Fuzzy, Neutrosophic, and Plithogenic Sets, into Large Language Models (LLMs). It proposes innovative models like Large Uncertain Language Models and Natural Uncertain Language Processing, integrating hierarchical and generalized structures to advance the handling of uncertainty in linguistic representation and processing. Chapter 5 introduces the Natural n-Superhyper Plithogenic Language by synthesizing natural language, plithogenic frameworks, and superhyperstructures. This innovative construct seeks to address challenges in advanced linguistic and structural modeling, blending attributes of uncertainty, complexity, and hierarchical abstraction. Chapter 6 defines mathematical extensions such as NeutroHyperstructures and AntiHyperstructures using the Neutrosophic Triplet framework. It formalizes structures like neutro-superhyperstructures, advancing classical frameworks into higher-dimensional realms. Chapter 7 explores the extension of Binary Code, Gray Code, and Floorplans through hyperstructures and superhyperstructures. It highlights their iterative and hierarchical applications, demonstrating their adaptability for complex data encoding and geometric arrangement challenges. Chapter 8 investigates the Neutrosophic TwoFold SuperhyperAlgebra, combining classical algebraic operations with neutrosophic components. This chapter expands upon existing algebraic structures like Hyperalgebra and AntiAlgebra, exploring hybrid frameworks for advanced mathematical modeling. Chapter 9 introduces Hyper Z-Numbers and SuperHyper Z-Numbers by extending the traditional Z-Number framework with hyperstructures. These extensions aim to represent uncertain information in more complex and multidimensional contexts. Chapter 10 revisits category theory through the lens of hypercategories and superhypercategories. By incorporating hierarchical and iterative abstractions, this chapter extends the foundational principles of category theory to more complex and layered structures. Chapter 11 formalizes the concept of n-SuperHyperBranch-width and its theoretical properties. By extending hypergraphs into superhypergraphs, the chapter explores recursive structures and their potential for representing intricate hierarchical relationships. Chapter 12 examines superhyperstructures of partitions, integrals, and spaces, proposing a framework for advancing mathematical abstraction. It highlights the potential applications of these generalizations in addressing hierarchical and multi-layered problems. Chapter 13 revisits Rough, HyperRough, and SuperHyperRough Sets, introducing new concepts like Tree-HyperRough Sets. The chapter connects these frameworks to advanced approaches for modeling uncertainty and complex relationships. Chapter 14 explores Plithogenic SuperHyperStructures and their applications in decision-making, control, and neuro systems. By integrating these advanced frameworks, the chapter proposes innovative directions for extending existing systems to handle multi-attribute and contradictory properties. Chapter 15 focuses on superhypergraphs, expanding hypergraph concepts to model complex structural types like arboreal and molecular superhypergraphs. It introduces Generalized n-th Powersets as a unifying framework for broader mathematical applications, while also touching on hyperlanguage processing. Chapter 16 defines NeutroHypergeometry and AntiHypergeometry as extensions of classical geometric structures. Using the Geometric Neutrosophic Triplet, the chapter demonstrates the flexibility of these frameworks in representing multi-dimensional and uncertain relationships. Chapter 17 establishes the theoretical groundwork for SuperHyperGraph Neural Networks and Plithogenic Graph Neural Networks. By integrating advanced graph structures, this chapter opens pathways for applying neural networks to more intricate and uncertain data representations.
Cognitive Computing Recipes
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Author : Adnan Masood
language : en
Publisher: Apress
Release Date : 2019-03-27
Cognitive Computing Recipes written by Adnan Masood and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-27 with Computers categories.
Solve your AI and machine learning problems using complete and real-world code examples. Using a problem-solution approach, this book makes deep learning and machine learning accessible to everyday developers, by providing a combination of tools such as cognitive services APIs, machine learning platforms, and libraries. Along with an overview of the contemporary technology landscape, Machine Learning and Deep Learning with Cognitive Computing Recipes covers the business case for machine learning and deep learning. Covering topics such as digital assistants, computer vision, text analytics, speech, and robotics process automation this book offers a comprehensive toolkit that you can apply quickly and easily in your own projects. With its focus on Microsoft Cognitive Services offerings, you’ll see recipes using multiple different environments including TensowFlow and CNTK to give you a broader perspective of the deep learning ecosystem. What You Will Learn Build production-ready solutions using Microsoft Cognitive Services APIs Apply deep learning using TensorFlow and Microsoft Cognitive Toolkit (CNTK) Solve enterprise problems in natural language processing and computer vision Discover the machine learning development life cycle – from formal problem definition to deployment at scale Who This Book Is For Software engineers and enterprise architects who wish to understand machine learning and deep learning by building applications and solving real-world business problems.
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Author : عبدالله بن يحيي الفيفي
language : ar
Publisher: مجمع الملك سلمان العالمي للغة العربية
Release Date : 2024-06-01
written by عبدالله بن يحيي الفيفي and has been published by مجمع الملك سلمان العالمي للغة العربية this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-01 with Foreign Language Study categories.
يُصدر مجمع الملك سلمان العالمي للغة العربية هذا الكتاب ضمن سلسلة (مباحث لغوية)، وذلك وفق خطة عمل مقسمة إلى مراحل لموضوعات علمية رأى المجمع حاجة المكتبة اللغوية العربية إليها أو إلى بدء النشاط البحثي فيها، واجتهد في استكتاب نخبة من المحررين والمؤلفين للنهوض بعناوين هذه السلسلة على أكمل وجه. ويهدف المجمع من وراء ذلك إلى تنشيط العمل في المجالات التي تُنَبِّه إليها هذه السلسلة، سواء أكان العمل علميا بحثيا، أم عمليا تنفيذيا، ويدعو المجمع الباحثين كافة من أنحاء العالم إلى المساهمة في هذه السلسلة. والشكر والتقدير الوافر لسمو وزير الثقافة رئيس مجلس أمناء المجمع الذي يحث على كل ما من شأنه تثبيت الهوية اللغوية العربية، وتمتينها، وفق رؤية استشرافية محققة لتوجيهات قيادتنا الحكيمة. والدعوة موجّهة إلى جميع المختصين والمهتمين للتواصل مع المجمع: لبناء المشروعات العلمية، وتكثيف الجهود والتكامل نحو تمكين لغتنا العربية، وتحقيق وجودها السامي في مجالات الحياة.
Linguistic Fundamentals For Natural Language Processing
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Author : Emily M. Bender
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2013-06-01
Linguistic Fundamentals For Natural Language Processing written by Emily M. Bender and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-01 with Computers categories.
Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages
Natural Language Processing Cookbook
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Author : Rosario Moscato
language : en
Publisher: BPB Publications
Release Date : 2025-02-26
Natural Language Processing Cookbook written by Rosario Moscato and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-26 with Computers categories.
DESCRIPTION Natural language processing (NLP) is revolutionizing how machines understand and interact with human language, creating powerful applications from chatbots to text analytics. This provides a practical, hands-on approach to mastering these technologies, making complex NLP concepts accessible through step-by-step recipes and real-world examples. This book walks you through the world of teaching computers to understand human language, starting with the basics and building up to advanced techniques. You will learn how to break down text into meaningful pieces, use Python programming to handle text data, and clean up messy text for analysis. The book shows you how computers can understand the meaning behind words using methods like word embeddings and BERT. You will discover how to identify parts of speech and recognize names of people and places in text, and how to sort text into different categories using ML. Advanced topics include finding hidden themes in document collections, building chatbots that can have conversations, and creating visual representations of text data. Throughout the book, practical Python examples help you implement these techniques while considering how to evaluate and deploy real-world NLP systems. By the time you complete this book, you will possess the technical proficiency to implement complete NLP pipelines from preprocessing to deployment. The recipe-based approach ensures you can immediately apply these techniques to solve real business problems. KEY FEATURES ● Step-by-step approach for each technique, with practical examples to fully master NLP. ● Add value to your data by mastering the most important NLP techniques. ● Readily usable recipes for implementing basic tasks like data cleaning and tokenization to more complicated neural network implementations. WHAT YOU WILL LEARN ● Preprocess and clean text for accurate NLP model performance. ● Apply ML techniques for text classification tasks. ● Extract key insights using semantic analysis and embeddings. ● Develop and fine-tune topic modeling algorithms. ● Build intelligent chatbots with dialogue management and intent detection. ● Visualize text data with word clouds and entity graphs. WHO THIS BOOK IS FOR This book is ideal for data scientists, programmers, business analysts, and students with basic Python knowledge who want to build practical NLP skills. Whether you are an AI enthusiast looking to enter the field or a professional seeking to add language processing capabilities to your toolkit, you will find actionable recipes that bridge theory and application. TABLE OF CONTENTS 1. Getting Started with NLP 2. Python for Text Processing 3. Text Processing and Cleaning 4. Semantic Representation 5. Part-of-speech Tagging and Named Entity Recognition 6. Text Classification 7. Advanced Techniques for Topic Modeling 8. Building a Chatbot 9. Text Data Visualization Techniques 10. Conclusion and Takeaways
Building Search Applications
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Author : Manu Konchady
language : en
Publisher: Lulu.com
Release Date : 2008
Building Search Applications written by Manu Konchady and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
Lucene, LingPipe, and Gate are popular open source tools to build powerful search applications. Building Search Applications describes functions from Lucene that include indexing, searching, ranking, and spelling correction to build search engines. With this book you will learn to: Extract tokens from text using custom tokenizers and analyzers from Lucene, LingPipe, and Gate. Construct a search engine index with an optional backend database to manage large document collections. Explore the wide range of Lucene queries to search an index, understand the ranking algorithm for a query, and suggest spelling corrections. Find the names of people, places, and other entities in text using LingPipe and Gate. Categorize documents by topic using classifiers and build groups of self-organized documents using clustering algorithms from LingPipe. Create a Web crawler to scan the Web, Intranet, or desktop using Nutch. Track the sentiment of articles published on the Web with LingPipe.