DocumentCode :
130829
Title :
A method of pre-sentence text based on Map/Reduce storage and indexing classification
Author :
Wu Qing ; Yu Yue ; Yao Yi ; Wu Liang
Author_Institution :
Dept. of Comput. Sci. & Technol., Hangzhou Dianzi Univ., Hangzhou, China
fYear :
2014
fDate :
27-29 June 2014
Firstpage :
195
Lastpage :
199
Abstract :
Today, as more and more businesses and individuals into the study of cloud computing, data storage in the cloud platform is also growing. So how cloud environment quickly and effectively store, manage and use these data has become a very important and challenging issues. This paper mainly discusses the storage model based on Map/Reduce text categorization, at the same time combining forecasting data classification strategy, classifying the data in the cloud storage system, the hot data stored in the hot disk area, the cold disk data stored in the cold area, and neural network to predict seasonal data, to predict the temperature data in the next period of time, the data in the hot or cold area can be seasonal migration in the region. Indexing based on this model, which can improve the efficiency of huge amounts of data indexing. To a certain extent, reduce query latency and improve search efficiency.
Keywords :
classification; cloud computing; data handling; database indexing; neural nets; query processing; storage management; text analysis; Map-Reduce storage; Map-Reduce text categorization; cloud computing; cloud storage system; cold disk data; data indexing; data storage; forecasting data classification strategy; hot disk data; indexing classification; neural network; presentence text classification; query latency; seasonal data prediction; temperature data prediction; Algorithm design and analysis; Classification algorithms; Cloud computing; Indexing; Temperature distribution; Text categorization; Cloud storage; Map/Reduce; data index; pre-sentence text classification; weights;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
ISSN :
2327-0586
Print_ISBN :
978-1-4799-3278-8
Type :
conf
DOI :
10.1109/ICSESS.2014.6933543
Filename :
6933543
Link To Document :
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