DocumentCode
1576429
Title
A Novel Method of Parallel GPU Implementation of KNN Used in Text Classification
Author
Lican Huang ; Zhilong Li
Author_Institution
Sch. of Inf., Zhejiang Sci-Tech Univ., Hangzhou, China
fYear
2013
Firstpage
6
Lastpage
8
Abstract
Automatic text classification is useful when websites have huge volume of web pages or other articles. K-Nearest Neighbour (KNN) is a way to classify the domains of text documents. The performance of text classification depends on lots of factors but KNN process contributes most of computational loads. We present a novel method of parallel GPU implementation of KNN with speed-ups of 40 times compared with CPU implementation.
Keywords
Web sites; graphics processing units; pattern classification; text analysis; CPU implementation; KNN; Website; automatic text classification; k-nearest neighbour; parallel GPU implementation; text documents; Central Processing Unit; Graphics processing units; Informatics; Parallel algorithms; Partitioning algorithms; Text categorization; Vectors; GPU; KNN; Parallel Computing; Text Classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Networking and Distributed Computing (ICNDC), 2013 Fourth International Conference on
Conference_Location
Los Angeles, CA
ISSN
2165-4999
Print_ISBN
978-1-4799-3045-6
Type
conf
DOI
10.1109/ICNDC.2013.20
Filename
6919844
Link To Document