Data Science Third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017, Changsha, China, September 22–24, 2017, Proceedings, Part II /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Zou, Beiji (Επιμελητής έκδοσης), Han, Qilong (Επιμελητής έκδοσης), Sun, Guanglu (Επιμελητής έκδοσης), Jing, Weipeng (Επιμελητής έκδοσης), Peng, Xiaoning (Επιμελητής έκδοσης), Lu, Zeguang (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2017.
• Σειρά: Communications in Computer and Information Science, 728
• Θέματα: Computer science.; Data mining.; Artificial intelligence.; Image processing.; Pattern recognition.; Computer Science.; Data Mining and Knowledge Discovery.; Artificial Intelligence (incl. Robotics).; Image Processing and Computer Vision.; Pattern Recognition.

This two volume set (CCIS 727 and 728) constitutes the refereed proceedings of the Third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017 (originally ICYCSEE) held in Changsha, China, in September 2017.  The 112 revised full papers presented in these...

Πίνακας περιεχομένων:

• Mathematical Issues in Data Science
•  Computational Theory for Data Science, Big Data Management and Applications
• Data Quality and Data Preparation
• Evaluation and Measurement in Data Science
• Data Visualization
• Big Data Mining and Knowledge Management
• Infrastructure for Data Science
• Machine Learning for Data Science
• Data Security and Privacy
• Applications of Data Science
• Case Study of Data Science
• Multimedia Data Management and Analysis
• Data-driven Scientific Research
• Data-driven Bioinformatics
• Data-driven Healthcare
• Data-driven Management
• Data-driven eGovernment
• Data-driven Smart City/Planet
• Data Marketing and Economics
• Social Media and Recommendation Systems
• Data-driven Security
• Data-driven Business Model Innovation
• Social and/or organizational impacts of Data Science.