Pricelists.org Pricelists.org

Knowledge Graphs and Big Data Processing

☆☆☆☆☆ (0 reviews)
Show price history
Knowledge Graphs and Big Data Processing
Lowest price (incl. delivery)
56,59 EUR
Typical price43,64 PLN
Lowest (90 days)41,59 PLN
Offers3
Last updated1ヶ月前
See best offer
Price history (90 days)
Full history
2026-08-08 2026-08-14
価格推移
更新日時価格
2026-08-0841,59
2026-08-1441,59
Springer Nature Author Product price 41,59 EUR Delivery 15,00 EUR 合計 56,59 EUR 在庫状況 在庫あり Updated 1ヶ月前 View offer
SpringerNatureLink Shop INT Product price 47,19 EUR ▲ 8,3% Delivery free 合計 47,19 EUR 在庫状況 在庫あり Updated 3週間前 View offer
OnBuy.com Product price 48,80 GBP Delivery 15,00 GBP 合計 63,80 GBP 在庫状況 在庫あり Updated 1ヶ月前 View offer

価格や在庫状況は変更される場合があります。 最終更新: 08.08.2026 08:26.

EAN 9783030531980
Springer Nature
0,0
☆☆☆☆☆
0 reviews
5★ 0%
4★ 0%
3★ 0%
2★ 0%
1★ 0%

Product reviews

Rating
No reviews yet — be the first!
This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.

Similar products