Data Mining and Big Data

The LNCS volume LNCS 9714 constitutes the refereed proceedings of the International Conference on Data Mining and Big Data, DMBD 2016, held in Bali, Indonesia, in June 2016.
The 57 papers presented in this volume were carefully reviewed and selected from 115 submissions. The theme of DMBD 2016 is "Serving Life with Data Science". Data mining refers to the activity of going through big data sets to look for relevant or pertinent information.The papers are organized in 10 cohesive sections covering all major topics of the research and development of data mining and big data and one Workshop on Computational Aspects of Pattern Recognition and Computer Vision.

Includes supplementary material: sn.pub/extras

Inhalt
Challenges in Data Mining and Big Data.- Data Mining Algorithms.- Frequent Itemset Mining.- Spatial Data Mining.- Prediction.- Feature Selection.- Information Extraction.- Classification.- Anomaly Pattern and Diagnosis.- Data Visualization Analysis.- Privacy Policy.- Social Media.- Query Optimization and Processing Algorithm.- Big Data.- Computational Aspects of Pattern Recognition and Computer Vision.