Data Mining and Knowledge Discovery for Big Data Methodologies, Challenge and Opportunities /

The field of data mining has made significant and far-reaching advances over the past three decades.  Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of t...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Chu, Wesley W. (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Σειρά:Studies in Big Data, 1
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03485nam a22004575i 4500
001 978-3-642-40837-3
003 DE-He213
005 20151125231248.0
007 cr nn 008mamaa
008 130924s2014 gw | s |||| 0|eng d
020 |a 9783642408373  |9 978-3-642-40837-3 
024 7 |a 10.1007/978-3-642-40837-3  |2 doi 
040 |d GrThAP 
050 4 |a Q342 
072 7 |a UYQ  |2 bicssc 
072 7 |a COM004000  |2 bisacsh 
082 0 4 |a 006.3  |2 23 
245 1 0 |a Data Mining and Knowledge Discovery for Big Data  |h [electronic resource] :  |b Methodologies, Challenge and Opportunities /  |c edited by Wesley W. Chu. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2014. 
300 |a X, 311 p. 99 illus., 29 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Studies in Big Data,  |x 2197-6503 ;  |v 1 
505 0 |a Aspect and Entity Extraction for Opinion Mining -- Mining Periodicity from Dynamic and Incomplete Spatiotemporal Data -- Spatio-Temporal Data Mining for Climate Data: Advances, Challenges -- Mining Discriminative Subgraph Patterns from Structural Data -- Path Knowledge Discovery: Multilevel Text Mining as a Methodology for Phenomics -- InfoSearch: A Social Search Engine -- Social Media in Disaster Relief: Usage Patterns, Data Mining Tools, and Current Research Directions -- A Generalized Approach for Social Network Integration and Analysis with Privacy Preservation -- A Clustering Approach to Constrained Binary Matrix Factorization. 
520 |a The field of data mining has made significant and far-reaching advances over the past three decades.  Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease.  Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization. 
650 0 |a Engineering. 
650 0 |a Artificial intelligence. 
650 0 |a Computational intelligence. 
650 1 4 |a Engineering. 
650 2 4 |a Computational Intelligence. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
700 1 |a Chu, Wesley W.  |e editor. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642408366 
830 0 |a Studies in Big Data,  |x 2197-6503 ;  |v 1 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-40837-3  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)