menu
{ "item_title" : "Keyword Extraction", "item_author" : [" Taeho Jo "], "item_description" : "This book is concerned with numerical vector-based machine learning algorithms which are applied to keyword extraction. The book is authored by collecting slides about the application of machine learning algorithms to keyword extraction; each page is given as a slide. This book is intended for ones who study applications of machine learning algorithms to keyword extraction and is composed of five sections. Keyword extraction is defined as the process of extracting important words selectively from a text. This book covers the four machine learning algorithms, KNN Algorithm, Na ve Bayes, Learning Vector Quantization, and Perceptron, as approaches to keyword extraction.", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/79/834/577/9798345774915_b.jpg", "price_data" : { "retail_price" : "55.00", "online_price" : "55.00", "our_price" : "55.00", "club_price" : "55.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Keyword Extraction|Taeho Jo

Keyword Extraction : Numerical Vector based Approaches

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

This book is concerned with numerical vector-based machine learning algorithms which are applied to keyword extraction. The book is authored by collecting slides about the application of machine learning algorithms to keyword extraction; each page is given as a slide. This book is intended for ones who study applications of machine learning algorithms to keyword extraction and is composed of five sections. Keyword extraction is defined as the process of extracting important words selectively from a text. This book covers the four machine learning algorithms, KNN Algorithm, Na ve Bayes, Learning Vector Quantization, and Perceptron, as approaches to keyword extraction.

This item is Non-Returnable

Details

  • ISBN-13: 9798345774915
  • ISBN-10: 9798345774915
  • Publisher: Independently Published
  • Publish Date: November 2024
  • Dimensions: 9 x 6 x 0.15 inches
  • Shipping Weight: 0.23 pounds
  • Page Count: 70

Related Categories

You May Also Like...

    1

BAM Customer Reviews