- We will send in 10–14 business days.
/images/books/14777366/9783658458768.jpg)
- Author: Tek Raj Chhetri
- Publisher: Springer Vieweg
- ISBN-10: 3658458763
- ISBN-13: 9783658458768
- Format: 14.8 x 21 x 1.8 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
Improving Decision Making Using Semantic Web Technologies (e-book) (used book) | bookbook.eu
Reviews
Description
As technology becomes integral to our lives, its influence on decision making in smart cities, healthcare, and manufacturing is undeniable. However, challenges such as limited contextual awareness, domain knowledge, explainability of machine learning (ML), and issues of interoperability, data quality, and GDPR (General Data Protection Regulation) compliance in data sharing hinder effective decision making. This book addresses these critical challenges by exploring how the synergy of semantic technologies (SW), like ontologies and knowledge graphs, with or without ML, can overcome these challenges to improve decision making. Through real-world case studies in data sharing, manufacturing, and agriculture, it offers theoretical and practical insights and guidelines of how SW can enhance prediction accuracy, integrate domain knowledge, support ML explainability, and tackle interoperability, data quality, and GDPR challenges.
EXTRA 10 % discount with code: EXTRA
The promotion ends in 23d.03:22:04
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Tek Raj Chhetri
- Publisher: Springer Vieweg
- ISBN-10: 3658458763
- ISBN-13: 9783658458768
- Format: 14.8 x 21 x 1.8 cm, minkšti viršeliai
- Language: English English
As technology becomes integral to our lives, its influence on decision making in smart cities, healthcare, and manufacturing is undeniable. However, challenges such as limited contextual awareness, domain knowledge, explainability of machine learning (ML), and issues of interoperability, data quality, and GDPR (General Data Protection Regulation) compliance in data sharing hinder effective decision making. This book addresses these critical challenges by exploring how the synergy of semantic technologies (SW), like ontologies and knowledge graphs, with or without ML, can overcome these challenges to improve decision making. Through real-world case studies in data sharing, manufacturing, and agriculture, it offers theoretical and practical insights and guidelines of how SW can enhance prediction accuracy, integrate domain knowledge, support ML explainability, and tackle interoperability, data quality, and GDPR challenges.
Reviews