DocumentCode :
1734587
Title :
Ordered Segment for Classification of Big Data
Author :
Fatholahzadeh, A.
Author_Institution :
UMI GT, Supelec, Metz, France
Volume :
1
fYear :
2013
Firstpage :
268
Lastpage :
272
Abstract :
This paper presents a new, simple, and efficient data structure, namely, the ordered segment (OS): a mono dimensional string array that we have been using in our classification of big data. The essential idea in construction of OS is to make use of the redundancies that abound user-data. OS enables us to performs efficient retrieval, insertions and deletions of data. The theoretical and experimental observations show that the method presented is more practical than existing ones considering the use of dynamic string sets for the classifications of huge user-files.
Keywords :
Big Data; data structures; pattern classification; OS; big data classification; data deletion; data insertion; data retrieval; data structure; mono dimensional string array; ordered segment; Automata; Data structures; Decision trees; Learning automata; Syntactics; Time complexity; Transducers; Big Data; Information retrieval; Learning from text and multimedia;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2013 12th International Conference on
Conference_Location :
Miami, FL
Type :
conf
DOI :
10.1109/ICMLA.2013.54
Filename :
6784624
Link To Document :
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