Artificial intelligence for automated pricing based on product descriptions / Nguyen Thi Ngoc Anh, Tran Ngoc Thang, Vijender Kumar Solanki.
2022
HF5416.5 .A64 2022eb
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Details
Title
Artificial intelligence for automated pricing based on product descriptions / Nguyen Thi Ngoc Anh, Tran Ngoc Thang, Vijender Kumar Solanki.
ISBN
9789811647024 (electronic bk.)
981164702X (electronic bk.)
9789811647017 (print)
981164702X (electronic bk.)
9789811647017 (print)
Published
Singapore : Springer, 2022.
Language
English
Description
1 online resource (xv, 53 pages) : illustrations (some color)
Other Standard Identifiers
10.1007/978-981-16-4702-4 doi
Call Number
HF5416.5 .A64 2022eb
Dewey Decimal Classification
658.8/16
Summary
This book highlights artificial intelligence algorithms used in implementation of automated pricing. It presents the process for building automated pricing models from crawl data, preprocessed data to implement models, and their applications. The book also focuses on machine learning and deep learning methods for pricing, including from regression methods to hybrid and ensemble methods. The computational experiments are presented to illustrate the pricing processes and models.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file
PDF
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed September 1, 2021).
Series
SpringerBriefs in applied sciences and technology. Computational intelligence, 2625-3712
Available in Other Form
Print version: 9789811647017
Print version: 9789811647031
Print version: 9789811647031
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Online Access
Record Appears in
Online Resources > Ebooks
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Table of Contents
1. Pricing based on product descriptions: problem, data, and methods
2. Extract product data from descriptions by NLP techniques
3. Segmentation and Quantity the qualify features
4. Pricing prediction using machine learning and ensemble methods
5. Applications & Discussions.
2. Extract product data from descriptions by NLP techniques
3. Segmentation and Quantity the qualify features
4. Pricing prediction using machine learning and ensemble methods
5. Applications & Discussions.