Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Text Processing In Java
Download Text Processing In Java full books in PDF, epub, and Kindle. Read online Text Processing In Java ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Text Processing in Java by : Mitzi Morris
Download or read book Text Processing in Java written by Mitzi Morris and published by . This book was released on 2014-01-01 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book teaches you how to master the subtle art of multilingual text processing and prevent text data corruption. It provides an introduction to natural language processing using Lucene and Solr. It gives you tools and techniques to manage large collections of text data, whether they come from news feeds, databases, or legacy documents. Each chapter contains executable programs that can also be used for text data forensics. Topics covered: Unicode code points Character encodings from ASCII and Big5 to UTF-8 and UTF-32LE Character normalization using International Components for Unicode (ICU) Java I/O, including working directly with zip, gzip, and tar files Regular expressions in Java Transporting text data via HTTP Parsing and generating XML, HTML, and JSON Using Lucene 4 for natural language search and text classification Search, spelling correction, and clustering with Solr 4 Other books on text processing presuppose much of the material covered in this book. They gloss over the details of transforming text from one format to another and assume perfect input data. The messy reality of raw text will have you reaching for this book again and again.
Book Synopsis Learning Processing by : Daniel Shiffman
Download or read book Learning Processing written by Daniel Shiffman and published by Newnes. This book was released on 2015-09-09 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning Processing, Second Edition, is a friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages. Requiring no previous experience, this book is for the true programming beginner. It teaches the basic building blocks of programming needed to create cutting-edge graphics applications including interactive art, live video processing, and data visualization. Step-by-step examples, thorough explanations, hands-on exercises, and sample code, supports your learning curve. A unique lab-style manual, the book gives graphic and web designers, artists, and illustrators of all stripes a jumpstart on working with the Processing programming environment by providing instruction on the basic principles of the language, followed by careful explanations of select advanced techniques. The book has been developed with a supportive learning experience at its core. From algorithms and data mining to rendering and debugging, it teaches object-oriented programming from the ground up within the fascinating context of interactive visual media. This book is ideal for graphic designers and visual artists without programming background who want to learn programming. It will also appeal to students taking college and graduate courses in interactive media or visual computing, and for self-study. A friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages No previous experience required—this book is for the true programming beginner! Step-by-step examples, thorough explanations, hands-on exercises, and sample code supports your learning curve
Book Synopsis Natural Language Processing with Java by : Richard M Reese
Download or read book Natural Language Processing with Java written by Richard M Reese and published by Packt Publishing Ltd. This book was released on 2015-03-27 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Java for Data Science by : Richard M. Reese
Download or read book Java for Data Science written by Richard M. Reese and published by Packt Publishing Ltd. This book was released on 2017-01-10 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examine the techniques and Java tools supporting the growing field of data science About This Book Your entry ticket to the world of data science with the stability and power of Java Explore, analyse, and visualize your data effectively using easy-to-follow examples Make your Java applications more capable using machine learning Who This Book Is For This book is for Java developers who are comfortable developing applications in Java. Those who now want to enter the world of data science or wish to build intelligent applications will find this book ideal. Aspiring data scientists will also find this book very helpful. What You Will Learn Understand the nature and key concepts used in the field of data science Grasp how data is collected, cleaned, and processed Become comfortable with key data analysis techniques See specialized analysis techniques centered on machine learning Master the effective visualization of your data Work with the Java APIs and techniques used to perform data analysis In Detail Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this book, we cover the important data science concepts and how they are supported by Java, as well as the often statistically challenging techniques, to provide you with an understanding of their purpose and application. The book starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. The next section examines the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. The final chapter illustrates an in-depth data science problem and provides a comprehensive, Java-based solution. Due to the nature of the topic, simple examples of techniques are presented early followed by a more detailed treatment later in the book. This permits a more natural introduction to the techniques and concepts presented in the book. Style and approach This book follows a tutorial approach, providing examples of each of the major concepts covered. With a step-by-step instructional style, this book covers various facets of data science and will get you up and running quickly.
Download or read book Text Mining written by Taeho Jo and published by Springer. This book was released on 2018-06-07 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections. The author provides the guidelines for implementing text mining systems in Java, as well as concepts and approaches. The book starts by providing detailed text preprocessing techniques and then goes on to provide concepts, the techniques, the implementation, and the evaluation of text categorization. It then goes into more advanced topics including text summarization, text segmentation, topic mapping, and automatic text management.
Book Synopsis Fundamentals of Computer Programming with C# by : Svetlin Nakov
Download or read book Fundamentals of Computer Programming with C# written by Svetlin Nakov and published by Faber Publishing. This book was released on 2013-09-01 with total page 1132 pages. Available in PDF, EPUB and Kindle. Book excerpt: The free book "Fundamentals of Computer Programming with C#" is a comprehensive computer programming tutorial that teaches programming, logical thinking, data structures and algorithms, problem solving and high quality code with lots of examples in C#. It starts with the first steps in programming and software development like variables, data types, conditional statements, loops and arrays and continues with other basic topics like methods, numeral systems, strings and string processing, exceptions, classes and objects. After the basics this fundamental programming book enters into more advanced programming topics like recursion, data structures (lists, trees, hash-tables and graphs), high-quality code, unit testing and refactoring, object-oriented principles (inheritance, abstraction, encapsulation and polymorphism) and their implementation the C# language. It also covers fundamental topics that each good developer should know like algorithm design, complexity of algorithms and problem solving. The book uses C# language and Visual Studio to illustrate the programming concepts and explains some C# / .NET specific technologies like lambda expressions, extension methods and LINQ. The book is written by a team of developers lead by Svetlin Nakov who has 20+ years practical software development experience. It teaches the major programming concepts and way of thinking needed to become a good software engineer and the C# language in the meantime. It is a great start for anyone who wants to become a skillful software engineer. The books does not teach technologies like databases, mobile and web development, but shows the true way to master the basics of programming regardless of the languages, technologies and tools. It is good for beginners and intermediate developers who want to put a solid base for a successful career in the software engineering industry. The book is accompanied by free video lessons, presentation slides and mind maps, as well as hundreds of exercises and live examples. Download the free C# programming book, videos, presentations and other resources from http://introprogramming.info. Title: Fundamentals of Computer Programming with C# (The Bulgarian C# Programming Book) ISBN: 9789544007737 ISBN-13: 978-954-400-773-7 (9789544007737) ISBN-10: 954-400-773-3 (9544007733) Author: Svetlin Nakov & Co. Pages: 1132 Language: English Published: Sofia, 2013 Publisher: Faber Publishing, Bulgaria Web site: http://www.introprogramming.info License: CC-Attribution-Share-Alike Tags: free, programming, book, computer programming, programming fundamentals, ebook, book programming, C#, CSharp, C# book, tutorial, C# tutorial; programming concepts, programming fundamentals, compiler, Visual Studio, .NET, .NET Framework, data types, variables, expressions, statements, console, conditional statements, control-flow logic, loops, arrays, numeral systems, methods, strings, text processing, StringBuilder, exceptions, exception handling, stack trace, streams, files, text files, linear data structures, list, linked list, stack, queue, tree, balanced tree, graph, depth-first search, DFS, breadth-first search, BFS, dictionaries, hash tables, associative arrays, sets, algorithms, sorting algorithm, searching algorithms, recursion, combinatorial algorithms, algorithm complexity, OOP, object-oriented programming, classes, objects, constructors, fields, properties, static members, abstraction, interfaces, encapsulation, inheritance, virtual methods, polymorphism, cohesion, coupling, enumerations, generics, namespaces, UML, design patterns, extension methods, anonymous types, lambda expressions, LINQ, code quality, high-quality code, high-quality classes, high-quality methods, code formatting, self-documenting code, code refactoring, problem solving, problem solving methodology, 9789544007737, 9544007733
Book Synopsis Natural Language Processing with Java Cookbook by : Richard M. Reese
Download or read book Natural Language Processing with Java Cookbook written by Richard M. Reese and published by Packt Publishing Ltd. This book was released on 2019-04-25 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Text Processing in Python by : David Mertz
Download or read book Text Processing in Python written by David Mertz and published by Addison-Wesley Professional. This book was released on 2003 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: bull; Demonstrates how Python is the perfect language for text-processing functions. bull; Provides practical pointers and tips that emphasize efficient, flexible, and maintainable approaches to text-processing challenges. bull; Helps programmers develop solutions for dealing with the increasing amounts of data with which we are all inundated.
Book Synopsis Digital Image Processing by : Wilhelm Burger
Download or read book Digital Image Processing written by Wilhelm Burger and published by Springer Science & Business Media. This book was released on 2012-01-19 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written as an introduction for undergraduate students, this textbook covers the most important methods in digital image processing. Formal and mathematical aspects are discussed at a fundamental level and various practical examples and exercises supplement the text. The book uses the image processing environment ImageJ, freely distributed by the National Institute of Health. A comprehensive website supports the book, and contains full source code for all examples in the book, a question and answer forum, slides for instructors, etc. Digital Image Processing in Java is the definitive textbook for computer science students studying image processing and digital processing.
Book Synopsis Data-Intensive Text Processing with MapReduce by : Jimmy Lin
Download or read book Data-Intensive Text Processing with MapReduce written by Jimmy Lin and published by Springer Nature. This book was released on 2022-05-31 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks
Book Synopsis Learn By Examples - A Quick Guide to Java Programming for Text Mining and NLP by : Eric M. H. Goh
Download or read book Learn By Examples - A Quick Guide to Java Programming for Text Mining and NLP written by Eric M. H. Goh and published by SVBook. This book was released on 2018-06-15 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aim to equip the reader with Java Programming, Text Mining and Natural Language Processing basics. There will be many examples and explanations that are lucid and straight to the point. You will be walked through various projects and develop your own text mining application. This book will show you how to use Stanford NLP libraries also. Asides, we have also uploaded some of our own softwares at: http://DSTK.Tech Content Covered: IntroductionGetting Started (Installing IDE, ...)Language Essentials I (variables, data types, ...)Language Essentials II (loops, if... else..., methods)Object Essentials (classes, inheritance, polymorphism, encapsulation, ...)Text Mining Essentials (Import Text Files, Text Transformation (lowercase, stopwords), Text Understanding (Stanford NLP), Text Classification (Stanford Classifier) )ISBN: 978-1-63535-546-8
Book Synopsis Mastering Java for Data Science by : Alexey Grigorev
Download or read book Mastering Java for Data Science written by Alexey Grigorev and published by Packt Publishing Ltd. This book was released on 2017-04-27 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. Style and approach This is a practical guide where all the important concepts such as classification, regression, and dimensionality reduction are explained with the help of examples.
Book Synopsis Natural Language Processing with Python by : Steven Bird
Download or read book Natural Language Processing with Python written by Steven Bird and published by "O'Reilly Media, Inc.". This book was released on 2009-06-12 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.
Book Synopsis Computational Linguistics and Intelligent Text Processing by : Alexander Gelbukh
Download or read book Computational Linguistics and Intelligent Text Processing written by Alexander Gelbukh and published by Springer. This book was released on 2003-06-29 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: CICLing 2001 is the second annual Conference on Intelligent text processing and Computational Linguistics (hence the name CICLing), see www.CICLing.org. It is intended to provide a balanced view of the cutting edge developments in both theoretical foundations of computational linguistics and practice of natural language text processing with its numerous applications. A feature of the CICLing conferences is their wide scope that covers nearly all areas of computational linguistics and all aspects of natural language processing applications. The conference is a forum for dialogue between the specialists working in these two areas. This year our invited speakers were Graeme Hirst (U. Toronto, Canada), Sylvain Kahane (U. Paris 7, France), and Ruslan Mitkov (U. Wolverhampton, UK). They delivered excellent extended lectures and organized vivid discussions. A total of 72 submissions were received, all but very few of surprisingly high quality. After careful reviewing, the Program Committee selected for presentation 53 of them, 41 as full papers and 12 as short papers, by 98 authors from 19 countries: Spain (19 authors), Japan (15), USA (12), France, Mexico (9 each), Sweden (6), Canada, China, Germany, Italy, Malaysia, Russia, United Arab Emirates (3 each), Argentina (2), Bulgaria, The Netherlands, Ukraine, UK, and Uruguay (1 each).
Book Synopsis Text Processing by : Allen B. Tucker
Download or read book Text Processing written by Allen B. Tucker and published by . This book was released on 1979 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction of text processing; Introduction to PL/1 for Text processing; Introduction to SNOBOL for text processing; Overview of text processing packages and applications.
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.
Book Synopsis Introduction to Linguistic Annotation and Text Analytics by : Graham Wilcock
Download or read book Introduction to Linguistic Annotation and Text Analytics written by Graham Wilcock and published by Morgan & Claypool Publishers. This book was released on 2009 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linguistic annotation and text analytics are active areas of research and development, with academic conferences and industry events such as the Linguistic Annotation Workshops and the annual Text Analytics Summits. This book provides a basic introduction to both fields, and aims to show that good linguistic annotations are the essential foundation for good text analytics. After briefly reviewing the basics of XML, with practical exercises illustrating in-line and stand-off annotations, a chapter is devoted to explaining the different levels of linguistic annotations. The reader is encouraged to create example annotations using the WordFreak linguistic annotation tool. The next chapter shows how annotations can be created automatically using statistical NLP tools, and compares two sets of tools, the OpenNLP and Stanford NLP tools. The second half of the book describes different annotation formats and gives practical examples of how to interchange annotations between different formats using XSLT transformations. The two main text analytics architectures, GATE and UIMA, are then described and compared, with practical exercises showing how to configure and customize them. The final chapter is an introduction to text analytics, describing the main applications and functions including named entity recognition, coreference resolution and information extraction, with practical examples using both open source and commercial tools. Copies of the example files, scripts, and stylesheets used in the book are available from the companion website, located at http: //sites.morganclaypool.com/wilcock. Table of Contents: Working with XML / Linguistic Annotation / Using Statistical NLP Tools / Annotation Interchange / Annotation Architectures / Text Analytics
