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Text Processing History

Text ProcessingLearn basics of Text Processing

In the world of computing, text processing means the methods of manipulating or creating electronic text. is a great place to start learning or improve your text processing skills with a section dedicated to text processing tutorials and resources. Here you can watch how text processing work. You can also search for text processing topic in our video library and premium projects. Join the community and improve your career prospects!


Text Processing Introduction

In the world of computing, text processing refers to methods of manipulating or creating electronic text. This discipline is quite popular among companies as it offers them good insight on what is going on around them. Text, in this case, refers to the alphanumeric characters that a person types with his/her keyboard. Technically, the text can be an abstraction layer over one of the standard character encoding. The process of manipulating or creating of data is known as text processing.

History of Text Processing

Regular language first saw the the use of text processing. It is the result of computer test processing with Klenne’s formalizing.

Text Processing Tools

To work effectively, you need to use tools. There are plenty of text processing tools online to get work done. Let’s list the 5 best text processing tools.You can also check the list of processing tools.

  • General-Purpose Preprocessors:- m4, filepp, chpp, GPP.
  • General-Purpose template systems:- Jinja2, eRuby, HTML-Template, Cheetah, Smarty.
  • Parser Generators: Regexp::Grammars, Marpa, ANTLR, Yaac, Lemon Parser Generator.
  • Diffing and Patching Tools: GNU patch, comm, Meld, GNU wdiff.
  • XML Processors: XQuery, SAXON, XML transformation languages
  • Standard UNIX Text Processing Tools: - tail, paste, head, sed, grep.

Education Ecosystem Text Processing Project Creators

If you are wondering where to get started to learn Text Processing, our recommendation will be to watch Text Processing Project Creators on Education Ecosystem. Let’s list the top 5 Text Processing Project Creators on Education Ecosystem.

Project Creators!

Text Processing Best Books

There are plenty of text processing books available online. The best way to start learning text processing is to invest in the books. So, why the wait? Let’s go through the best books for learning text processing. These books are categorized into Beginner, Intermediate and Advanced. So pick the book that best suits you.

  • Book cover

    Python 2.6 Text Processing: Beginners Guide

    by Jeff McNeil

    With a basic knowledge of Python you have the potential to undertake time-saving text processing. This book is a great introduction to the various techniques, and teaches through practical examples and clear explanations.

  • Book cover

    Text Processing in Java

    by Mitzi Morris

    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.

  • Book cover

    Text Processing in Python

    by David Mertz

    Filled with concrete examples, this book provides effective solutions to specific text processing problems and practical strategies for dealing with all types of text processing challenges. It provides the answers to questions such as: What is the best way to convert from binary to ASCII?; How do I work with full text indexing?; How do I find a URL or an email address in text?; What are the different levels of pattern matching?; How do I process a report with a concrete state machine?; How do I parse, create and manipulate HTML documents?; How do I handle a lossless and lossy compression?; And what is the most efficient way to find codepoints in Unicode?

  • Book cover

    Python 3 Text Processing with NLTK 3 Cookbook

    by Jacob Perkins

    This book will teach you how to break text down into its component parts for spelling correction, feature extraction, and phrase transformation. You will also learn how to do custom sentiment analysis and named entity recognition, work through the natural language processing concepts with simple and easy-to-follow programming recipes.

  • Book cover

    Text Processing with Ruby: Extract Value from the Data That Surrounds You

    by Rob Miller

    Text Processing with Ruby takes a practical approach. You'll learn how to get text into your Ruby programs from the file system and from user input. You'll process delimited files such as CSVs, and write utilities that interact with other programs in text-processing pipelines. Decipher character encoding mysteries, and avoid the pain of jumbled characters and malformed output.

  • Book cover

    Interactive Data Visualization for the Web: An Introduction to Designing with D3

    by Scott Murray

    The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You’ll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media.

Text Processing Projects

The best way to learn is to evolve yourself with Projects. Let’s look at some of the best Text Processing projects that you can follow. You can also find Text Processing projects on Education Ecosystem. If you are interested, check Education Ecosystem Text Processing Project Creators section for more information.

NLTK is all about building Python programs to work with human language data.

Explore this project!

This project uses the OpenNLP and offers multiple advanced tasks such as part of speech tagging, parsing, tokenization, etc.

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Taming Text is a great book for text processing. Grant S.Ingersoll writes the book is a great project on text processing. You can learn a lot from this open book.

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A rule-based sentence segmenter(splitter) and a word tokenizer using orthographic features.

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SUTime is a library for normalizing and recognizing time expressions.

Explore this project!

Text Processing Community

Text Processing has a universal presence and it is also evident from the community available. Not only you will find multiple websites that can help you meet up with like-minded people, but to also people in related field offline.

  • Kaggle This is the home of data related subjects. It is basically a home for data science which equates same love for text processing,
  • Education Ecosystem Here you can find all the awesome Project Creators who love to share their knowledge about Data Analytics.

Text Processing Gurus

  • Stephen Wolfram

    Fei Song

    Fei Song is a text processing expert who is interested in Artificial Intelligence, particularly in the fields of Natural Language Processing and Information Retrieval. He has conducted several projects in Text segmentation, Text summarization, Document Clustering and it Application to people search, Text categorization, Statistical methods for information retrieval, Temporal reasoning about plans and Medical information systems.

  • Eduard H. Hovy

    Eduard H. Hovy is an expert in Text Mining, Computational linguistics, language translation and Natural language processing. He is currently the Research Professor at the Language Technologies Institute of Carnegie Mellon University, Co- Director for Research of the Command, Control, and Interoperability Center for Advanced Data Analysis and a Regular High-Level Visiting Scientist, International Guest Academic Talents(IGAT) Program for the Development of University Disciplines in China.

    Eduard H. Hovy
  • Dunwei(Grant) Wen

    Dunwei(Grant) Wen

    Dunwei(Grant) Wen is an expert in Text Analysis, Artificial Intelligence, Data Mining, Machine Learning and Inference and Natural language processing. His recent research program aims to advance the theory and technology of natural language and knowledge processing especially semantic analysis that bridges the gap between language and knowledge, by the novel use of both machine learning and inference methods.

  • Kevin C. Knight

    Kevin C. Knight is a professor of Computer Science, School of Engineering, Research Director, Natural Language Group, Intelligent Systems Division, Information Science Institute. He is an expert in Text generation, natural language processing, natural language generation, cryptography, code breaking and more.

    Kevin C. Knight
  • Niels Kasch

    Niels Kasch

    Niels Kasch is an expert in Machine learning and information extraction specialist with a Ph.D. in computer science. He is experienced in working with web-scale data sources. He has extensive knowledge of natural processing and topic modeling as well as detailed knowledge of software engineering and best practices.

Text Processing Conferences

Since Text Processing is a trending topic in the market, there are many conferences out there that you can attend. Let’s list some of the best Text processing conferences out there.