New bloom filter architecture for string matching
Implementation of the Bloom filter for plagiarism detection in full text document has a problem on how to identify the same terms from different location.Location identifier can be hashed in offline mode since the collection is static.By this approach, the computation speed of the Bloom filter can b...
Saved in:
Main Authors: | , |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2008
|
Subjects: | |
Online Access: | http://repo.uum.edu.my/11363/1/349-352-CR154.pdf http://repo.uum.edu.my/11363/ http://www.kmice.uum.edu.my |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Universiti Utara Malaysia |
Language: | English |
id |
my.uum.repo.11363 |
---|---|
record_format |
eprints |
spelling |
my.uum.repo.113632014-07-24T03:48:03Z http://repo.uum.edu.my/11363/ New bloom filter architecture for string matching Sediyono, Agung Ku-Mahamud, Ku Ruhana QA76 Computer software Implementation of the Bloom filter for plagiarism detection in full text document has a problem on how to identify the same terms from different location.Location identifier can be hashed in offline mode since the collection is static.By this approach, the computation speed of the Bloom filter can be improved.Two new Bloom filter architectures are proposed in this study to overcome the problem of computational time.First architecture concatenates hash code of the string and its location identifier, while the second architecture concatenates the bit position of the string and its location identifier.Analysis was conducted to evaluate the proposed architectures in terms of computation time.From the result, computation time can be reduced if the location identifiers are hashed offline. 2008-05-10 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/11363/1/349-352-CR154.pdf Sediyono, Agung and Ku-Mahamud, Ku Ruhana (2008) New bloom filter architecture for string matching. In: Knowledge Management International Conference 2008 (KMICe2008), 10-12 June 2008, Langkawi, Malaysia. http://www.kmice.uum.edu.my |
institution |
Universiti Utara Malaysia |
building |
UUM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Utara Malaysia |
content_source |
UUM Institutionali Repository |
url_provider |
http://repo.uum.edu.my/ |
language |
English |
topic |
QA76 Computer software |
spellingShingle |
QA76 Computer software Sediyono, Agung Ku-Mahamud, Ku Ruhana New bloom filter architecture for string matching |
description |
Implementation of the Bloom filter for plagiarism detection in full text document has a problem on how to identify the same terms from different location.Location identifier can be hashed in offline mode since the collection is static.By this approach, the computation speed of the Bloom filter can be improved.Two new Bloom filter architectures are proposed in this study to overcome the problem of computational time.First architecture concatenates hash code of the string and its location identifier, while the second architecture concatenates the bit position of the string and its location identifier.Analysis was conducted to evaluate the proposed architectures in terms of computation time.From the result, computation time can be reduced if the location identifiers are hashed offline. |
format |
Conference or Workshop Item |
author |
Sediyono, Agung Ku-Mahamud, Ku Ruhana |
author_facet |
Sediyono, Agung Ku-Mahamud, Ku Ruhana |
author_sort |
Sediyono, Agung |
title |
New bloom filter architecture for string matching |
title_short |
New bloom filter architecture for string matching |
title_full |
New bloom filter architecture for string matching |
title_fullStr |
New bloom filter architecture for string matching |
title_full_unstemmed |
New bloom filter architecture for string matching |
title_sort |
new bloom filter architecture for string matching |
publishDate |
2008 |
url |
http://repo.uum.edu.my/11363/1/349-352-CR154.pdf http://repo.uum.edu.my/11363/ http://www.kmice.uum.edu.my |
_version_ |
1644280623805759488 |