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Data Mining and Big Data : First International Conference, DMBD 2016, Bali, Indonesia, June 25-30, 2016. Proceedings / edited by Ying Tan, Yuhui Shi.

SpringerLink Books Lecture Notes In Computer Science (LNCS) (1997-2024) Available online

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Format:
Book
Contributor:
Tan, Ying, 1964- editor.
Shi, Yuhui, editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 9714.
Information Systems and Applications, incl. Internet/Web, and HCI ; 9714
Language:
English
Subjects (All):
Pattern perception.
Artificial intelligence.
Application software.
Information storage and retrieval.
Database management.
Algorithms.
Pattern Recognition.
Artificial Intelligence.
Information Systems Applications (incl. Internet).
Information Storage and Retrieval.
Database Management.
Algorithm Analysis and Problem Complexity.
Local Subjects:
Pattern Recognition.
Artificial Intelligence.
Information Systems Applications (incl. Internet).
Information Storage and Retrieval.
Database Management.
Algorithm Analysis and Problem Complexity.
Physical Description:
1 online resource (XVI, 569 pages) : 141 illustrations.
Edition:
First edition 2016.
Contained In:
Springer eBooks
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2016.
System Details:
text file PDF
Summary:
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.
Contents:
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.
Other Format:
Printed edition:
ISBN:
978-3-319-40973-3
9783319409733
Access Restriction:
Restricted for use by site license.

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