Mastering Text Mining with R (notice n° 66123)
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| fixed length control field | 03442cam a2200289zu 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | FRCYB88843539 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250107220554.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250107s2016 fr | o|||||0|0|||eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781783551811 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | FRCYB88843539 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | FR-PaCSA |
| Language of cataloging | en |
| Transcribing agency | |
| Description conventions | rda |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Kumar, Ashish |
| 245 01 - TITLE STATEMENT | |
| Title | Mastering Text Mining with R |
| Statement of responsibility, etc. | ['Kumar, Ashish', 'Paul, Avinash'] |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Name of producer, publisher, distributor, manufacturer | Packt Publishing |
| Date of production, publication, distribution, manufacture, or copyright notice | 2016 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | p. |
| 336 ## - CONTENT TYPE | |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type code | c |
| Source | rdamdedia |
| 338 ## - CARRIER TYPE | |
| Carrier type code | c |
| Source | rdacarrier |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Master text-taming techniques and build effective text-processing applications with RAbout This BookDevelop all the relevant skills for building text-mining apps with R with this easy-to-follow guideGain in-depth understanding of the text mining process with lucid implementation in the R languageExample-rich guide that lets you gain high-quality information from text dataWho This Book Is ForIf you are an R programmer, analyst, or data scientist who wants to gain experience in performing text data mining and analytics with R, then this book is for you. Exposure to working with statistical methods and language processing would be helpful.What You Will LearnGet acquainted with some of the highly efficient R packages such as OpenNLP and RWeka to perform various steps in the text mining processAccess and manipulate data from different sources such as JSON and HTTPProcess text using regular expressionsGet to know the different approaches of tagging texts, such as POS tagging, to get started with text analysisExplore different dimensionality reduction techniques, such as Principal Component Analysis (PCA), and understand its implementation in RDiscover the underlying themes or topics that are present in an unstructured collection of documents, using common topic models such as Latent Dirichlet Allocation (LDA)Build a baseline sentence completing applicationPerform entity extraction and named entity recognition using RIn DetailText Mining (or text data mining or text analytics) is the process of extracting useful and high-quality information from text by devising patterns and trends. R provides an extensive ecosystem to mine text through its many frameworks and packages.Starting with basic information about the statistics concepts used in text mining, this book will teach you how to access, cleanse, and process text using the R language and will equip you with the tools and the associated knowledge about different tagging, chunking, and entailment approaches and their usage in natural language processing. Moving on, this book will teach you different dimensionality reduction techniques and their implementation in R. Next, we will cover pattern recognition in text data utilizing classification mechanisms, perform entity recognition, and develop an ontology learning framework.By the end of the book, you will develop a practical application from the concepts learned, and will understand how text mining can be leveraged to analyze the massively available data on social media.Style and approachThis book takes a hands-on, example-driven approach to the text mining process with lucid implementation in R. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Kumar, Ashish |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Paul, Avinash |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Access method | Cyberlibris |
| Uniform Resource Identifier | <a href="https://international.scholarvox.com/netsen/book/88843539">https://international.scholarvox.com/netsen/book/88843539</a> |
| Electronic format type | text/html |
| Host name | |
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