Data Analysis and Pattern Recognition in Multiple Databases

Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Adhikari, Animesh (Συγγραφέας), Adhikari, Jhimli (Συγγραφέας), Pedrycz, Witold (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2014.
Σειρά:Intelligent Systems Reference Library, 61
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
LEADER 03634nam a22005055i 4500
001 978-3-319-03410-2
003 DE-He213
005 20151103123513.0
007 cr nn 008mamaa
008 131206s2014 gw | s |||| 0|eng d
020 |a 9783319034102  |9 978-3-319-03410-2 
024 7 |a 10.1007/978-3-319-03410-2  |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 
100 1 |a Adhikari, Animesh.  |e author. 
245 1 0 |a Data Analysis and Pattern Recognition in Multiple Databases  |h [electronic resource] /  |c by Animesh Adhikari, Jhimli Adhikari, Witold Pedrycz. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2014. 
300 |a XV, 238 p. 97 illus.  |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 Intelligent Systems Reference Library,  |x 1868-4394 ;  |v 61 
505 0 |a From the Contents: Synthesizing Different Extreme Association Rules in Multiple Data Sources -- Clustering items in time-stamped databases induced by stability -- Mining global patterns in multiple large databases -- Clustering Local Frequency Items in Multiple Data Sources -- Mining Patterns of Select Items in Different Data Sources. 
520 |a Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyse them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery, and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments. 
650 0 |a Engineering. 
650 0 |a Data mining. 
650 0 |a Pattern recognition. 
650 0 |a Computational intelligence. 
650 1 4 |a Engineering. 
650 2 4 |a Computational Intelligence. 
650 2 4 |a Pattern Recognition. 
650 2 4 |a Data Mining and Knowledge Discovery. 
700 1 |a Adhikari, Jhimli.  |e author. 
700 1 |a Pedrycz, Witold.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783319034096 
830 0 |a Intelligent Systems Reference Library,  |x 1868-4394 ;  |v 61 
856 4 0 |u http://dx.doi.org/10.1007/978-3-319-03410-2  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)