Data, Engineering and Applications Volume 2 /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Shukla, Rajesh Kumar (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Agrawal, Jitendra (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Sharma, Sanjeev (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Singh Tomer, Geetam (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Θέματα: Big data.; Data mining.; Artificial intelligence.; Big Data.; Data Mining and Knowledge Discovery.; Artificial Intelligence.
• Φυσική περιγραφή: X, 343 p. 166 illus., 103 illus. in color. online resource.
• ISBN: 9789811363511
• DOI: 10.1007/978-981-13-6351-1

This book presents a compilation of current trends, technologies, and challenges in connection with Big Data. Many fields of science and engineering are data-driven, or generate huge amounts of data that are ripe for the picking. There are now more sources of data than ever before, and more means of capturing data. At the same time, the sheer volume and complexity of the data have sparked new developments, where many Big Data problems require new solutions. Given its scope, the book offers a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of Big Data applications.