KAL JAB MAIN NAHI RAHUNGA

Bangari Shravan Kumar

$51.95 $43.94

Hardback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

Unknown
22 July 2023

Mining technology & engineering; Computer science; Natural language & machine translation

Almost 80% of all data is generated in the real world, which generates a large volume of unstructured data. This unstructured data require complex processing methods, in contrast to organised data stored in databases. Text mining is an effective method for knowledge extraction and decision-making since it includes transforming unstructured text input into structured format. Classification, clustering, association rule mining, topic detection, and summarising are the main text mining tasks. This book examines cutting-edge text mining techniques and uses, such as customer relationship management, social network analysis, financial market forecasting, and document classification. Document classification, which incorporates programmes like phishing, malware, and spam detection, is one of the difficult challenges in text classification. The book suggests brand-new hybrid models for document categorization that work for both binary class and one-class problems, such as OCSVM-LSI, PCA-OCSVM, and LDA-CARM. The difficult task of stock market forecasting, which depends on unstructured news data, is also covered in the book. The suggested model predicts stock prices using a variety of regression approaches, including GMDH, GRNN, MLP, RPART, SVR, RF, and QRRF. The book provides insightful information on text mining's uses and how to make good decisions with it.

By: Bangari Shravan Kumar
Imprint: Unknown
Dimensions: Height: 229mm, Width: 152mm, Spine: 9mm
Weight: 231g
ISBN: 9788196481544
ISBN 10: 8196481543
Pages: 166
Publication Date: 22 July 2023
Audience: General/trade , ELT Advanced
Format: Hardback
Publisher's Status: Active

Reviews for KAL JAB MAIN NAHI RAHUNGA

I found Novel Text Mining Techniques and Applications to be an immensely informative and well-written book as a researcher in the subject of text mining. An detailed overview of the most recent developments in the topic is provided by the author, Bangari Shravan Kumar, along with useful applications that experts can use. I strongly advise it to everyone who is interested in text mining. Sara Thompson Anyone wishing to keep up with the most recent developments in text mining should read Bangari Shravan Kumar's Novel Text Mining Techniques and Applications. Both novice readers and seasoned professionals in the subject will find the book to be simple to understand. It's a great resource book for both researchers and practitioners because the author uses real-world examples and case studies. Rajesh Patel For my work as a data analyst, I found Novel Text Mining Techniques and Applications to be an immensely helpful book. The book is thorough and covers a wide range of subjects, from fundamental ideas to sophisticated methods. The book is rich with real-world examples and case studies that made it easier for me to understand the topics because of Bangari Shravan Kumar's engaging and understandable writing style. Everyone interested in text mining should definitely read this book, in my opinion. David Williams