By Ashish Kumar,Avinash Paul
- Develop all of the proper abilities for development text-mining apps with R with this easy-to-follow guide
- Gain in-depth knowing of the textual content mining approach with lucid implementation within the R language
- Example-rich consultant that permits you to achieve fine quality info from textual content data
Book DescriptionText Mining (or textual content facts mining or textual content analytics) is the method of extracting worthwhile and top of the range details from textual content by means of devising styles and traits. R offers an in depth environment to mine textual content via its many frameworks and packages.
Starting with uncomplicated information regarding the statistics strategies utilized in textual content mining, this publication will educate you ways to entry, cleanse, and procedure textual content utilizing the R language and may equip you with the instruments and the linked wisdom approximately assorted tagging, chunking, and entailment methods and their utilization in common language processing. relocating on, this booklet will educate you diversified dimensionality aid concepts and their implementation in R. subsequent, we are going to disguise development acceptance in textual content info using category mechanisms, practice entity recognition.
By the top of the booklet, you are going to increase a pragmatic program from the suggestions discovered, and may know the way textual content mining could be leveraged to research the hugely on hand information on social media.
What you'll learn
- Get familiar with the various hugely effective R applications akin to OpenNLP and RWeka to accomplish a variety of steps within the textual content mining process
- Access and control info from diversified resources reminiscent of JSON and HTTP
- Process textual content utilizing common expressions
- Get to grasp different ways of tagging texts, comparable to POS tagging, to start with textual content analysis
- Explore diversified dimensionality relief thoughts, corresponding to crucial part research (PCA), and comprehend its implementation in R
- Discover the underlying subject matters or subject matters which are found in an unstructured choice of records, utilizing universal subject types equivalent to Latent Dirichlet Allocation (LDA)
- Build a baseline sentence finishing application
- Perform entity extraction and named entity popularity utilizing R
About the AuthorAshish Kumar is an IIM alumnus and an engineer at middle. He has large event in facts technological know-how, computing device studying, and ordinary language processing having labored at businesses, comparable to McAfee-Intel, Volt consulting, an bold info technology startup ), and almost immediately linked to a prolific AI startup in FinTech area. Apart from paintings, Ashish additionally participates in facts technological know-how competitions at Kaggle in his spare time.
Avinash Paul is a programming language fanatic, loves exploring open assets applied sciences and programmer by means of selection. He has over 9 years of programming event. He has labored in Sabre Holdings , McAfee , Mindtree and has event in data-driven product improvement, He was once intrigued via info technology and information mining whereas constructing area of interest product in schooling house for an bold facts technology start-up. In his spare time he likes to learn technical books and educate underprivileged young ones again home.
Table of Contents
- Statistical Linguistics with R
- Processing Text
- Categorizing and Tagging Text
- Dimensionality Reduction
- Text Summarization and Clustering
- Text Classification
- Entity Recognition
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Key FeaturesDevelop all of the correct abilities for development text-mining apps with R with this easy-to-follow guideGain in-depth figuring out of the textual content mining technique with lucid implementation within the R languageExample-rich consultant that permits you to achieve top quality info from textual content dataBook DescriptionText Mining (or textual content information mining or textual content analytics) is the method of extracting invaluable and fine quality details from textual content by means of devising styles and traits.
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Mastering Text Mining with R by Ashish Kumar,Avinash Paul