Approximate string matching using compressed suffix arrays
Let T be a text of length n and P be a pattern of length m , both strings over a fixed finite alphabet A . The k -difference ( k -mismatch, respectively) problem is to find all occurrences of P in T that have edit distance (Hamming distance, respectively) at most k from P . In this paper we investig...
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| Veröffentlicht in: | Theoretical computer science 2006-03, Vol.352 (1), p.240-249 |
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| container_title | Theoretical computer science |
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| creator | Huynh, Trinh N.D. Hon, Wing-Kai Lam, Tak-Wah Sung, Wing-Kin |
| description | Let
T
be a text of length
n
and
P
be a pattern of length
m
, both strings over a fixed finite alphabet
A
. The
k
-difference (
k
-mismatch, respectively) problem is to find all occurrences of
P
in
T
that have edit distance (Hamming distance, respectively) at most
k
from
P
. In this paper we investigate a well-studied case in which
T
is fixed and preprocessed into an indexing data structure so that any pattern query can be answered faster. We give a solution using an
O
(
n
log
n
)
bits indexing data structure with
O
(
|
A
|
k
m
k
·
max
(
k
,
log
n
)
+
occ
)
query time, where
occ
is the number of occurrences. The best previous result requires
O
(
n
log
n
)
bits indexing data structure and gives
O
(
|
A
|
k
m
k
+
2
+
occ
)
query time. Our solution also allows us to exploit compressed suffix arrays to reduce the indexing space to
O
(
n
)
bits, while increasing the query time by an
O
(
log
n
)
factor only. |
| doi_str_mv | 10.1016/j.tcs.2005.11.022 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_28069572</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0304397505008716</els_id><sourcerecordid>28069572</sourcerecordid><originalsourceid>FETCH-LOGICAL-c401t-1f4420c96f7df7fb0bd5b2902fef45095add20e46cf3452e64130041496e65ff3</originalsourceid><addsrcrecordid>eNp9UD1PAzEMjRBIlMIPYOsC2x1OLsk1MFUVX1IlFpijNOdAqrZX4itq_z05tRIbHuw3vGf7PcauOZQcuL5blJ2nUgCokvMShDhhAz6uTSGEkadsABXIojK1OmcXRAvIpWo9YPeTzSa1u7hyHY6oS3H9OcrYf_VgS3337WqTkAibEW1DiLuRS8nt6ZKdBbckvDrOIft4enyfvhSzt-fX6WRWeAm8K3iQUoA3OtRNqMMc5o2aCwMiYJAKjHJNIwCl9qGSSqCWvAKQXBqNWoVQDdntYW9-9HuL1NlVJI_LpVtjuyUrxqCNqkUm8gPRp5YoYbCblI2lveVg-5TswuaUbJ-S5dzmlLLm5rjckXfLkNzaR_oT1koLwyHzHg48zE5_IiZLPuLaYxMT-s42bfznyi-j3Hyw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>28069572</pqid></control><display><type>article</type><title>Approximate string matching using compressed suffix arrays</title><source>Access via ScienceDirect (Elsevier)</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Huynh, Trinh N.D. ; Hon, Wing-Kai ; Lam, Tak-Wah ; Sung, Wing-Kin</creator><creatorcontrib>Huynh, Trinh N.D. ; Hon, Wing-Kai ; Lam, Tak-Wah ; Sung, Wing-Kin</creatorcontrib><description>Let
T
be a text of length
n
and
P
be a pattern of length
m
, both strings over a fixed finite alphabet
A
. The
k
-difference (
k
-mismatch, respectively) problem is to find all occurrences of
P
in
T
that have edit distance (Hamming distance, respectively) at most
k
from
P
. In this paper we investigate a well-studied case in which
T
is fixed and preprocessed into an indexing data structure so that any pattern query can be answered faster. We give a solution using an
O
(
n
log
n
)
bits indexing data structure with
O
(
|
A
|
k
m
k
·
max
(
k
,
log
n
)
+
occ
)
query time, where
occ
is the number of occurrences. The best previous result requires
O
(
n
log
n
)
bits indexing data structure and gives
O
(
|
A
|
k
m
k
+
2
+
occ
)
query time. Our solution also allows us to exploit compressed suffix arrays to reduce the indexing space to
O
(
n
)
bits, while increasing the query time by an
O
(
log
n
)
factor only.</description><identifier>ISSN: 0304-3975</identifier><identifier>EISSN: 1879-2294</identifier><identifier>DOI: 10.1016/j.tcs.2005.11.022</identifier><identifier>CODEN: TCSCDI</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Algorithmics. Computability. Computer arithmetics ; Applied sciences ; Computer science; control theory; systems ; Data processing. List processing. Character string processing ; Exact sciences and technology ; Memory organisation. Data processing ; Software ; Theoretical computing</subject><ispartof>Theoretical computer science, 2006-03, Vol.352 (1), p.240-249</ispartof><rights>2005 Elsevier B.V.</rights><rights>2006 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c401t-1f4420c96f7df7fb0bd5b2902fef45095add20e46cf3452e64130041496e65ff3</citedby><cites>FETCH-LOGICAL-c401t-1f4420c96f7df7fb0bd5b2902fef45095add20e46cf3452e64130041496e65ff3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.tcs.2005.11.022$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17562910$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Huynh, Trinh N.D.</creatorcontrib><creatorcontrib>Hon, Wing-Kai</creatorcontrib><creatorcontrib>Lam, Tak-Wah</creatorcontrib><creatorcontrib>Sung, Wing-Kin</creatorcontrib><title>Approximate string matching using compressed suffix arrays</title><title>Theoretical computer science</title><description>Let
T
be a text of length
n
and
P
be a pattern of length
m
, both strings over a fixed finite alphabet
A
. The
k
-difference (
k
-mismatch, respectively) problem is to find all occurrences of
P
in
T
that have edit distance (Hamming distance, respectively) at most
k
from
P
. In this paper we investigate a well-studied case in which
T
is fixed and preprocessed into an indexing data structure so that any pattern query can be answered faster. We give a solution using an
O
(
n
log
n
)
bits indexing data structure with
O
(
|
A
|
k
m
k
·
max
(
k
,
log
n
)
+
occ
)
query time, where
occ
is the number of occurrences. The best previous result requires
O
(
n
log
n
)
bits indexing data structure and gives
O
(
|
A
|
k
m
k
+
2
+
occ
)
query time. Our solution also allows us to exploit compressed suffix arrays to reduce the indexing space to
O
(
n
)
bits, while increasing the query time by an
O
(
log
n
)
factor only.</description><subject>Algorithmics. Computability. Computer arithmetics</subject><subject>Applied sciences</subject><subject>Computer science; control theory; systems</subject><subject>Data processing. List processing. Character string processing</subject><subject>Exact sciences and technology</subject><subject>Memory organisation. Data processing</subject><subject>Software</subject><subject>Theoretical computing</subject><issn>0304-3975</issn><issn>1879-2294</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2006</creationdate><recordtype>article</recordtype><recordid>eNp9UD1PAzEMjRBIlMIPYOsC2x1OLsk1MFUVX1IlFpijNOdAqrZX4itq_z05tRIbHuw3vGf7PcauOZQcuL5blJ2nUgCokvMShDhhAz6uTSGEkadsABXIojK1OmcXRAvIpWo9YPeTzSa1u7hyHY6oS3H9OcrYf_VgS3337WqTkAibEW1DiLuRS8nt6ZKdBbckvDrOIft4enyfvhSzt-fX6WRWeAm8K3iQUoA3OtRNqMMc5o2aCwMiYJAKjHJNIwCl9qGSSqCWvAKQXBqNWoVQDdntYW9-9HuL1NlVJI_LpVtjuyUrxqCNqkUm8gPRp5YoYbCblI2lveVg-5TswuaUbJ-S5dzmlLLm5rjckXfLkNzaR_oT1koLwyHzHg48zE5_IiZLPuLaYxMT-s42bfznyi-j3Hyw</recordid><startdate>20060307</startdate><enddate>20060307</enddate><creator>Huynh, Trinh N.D.</creator><creator>Hon, Wing-Kai</creator><creator>Lam, Tak-Wah</creator><creator>Sung, Wing-Kin</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20060307</creationdate><title>Approximate string matching using compressed suffix arrays</title><author>Huynh, Trinh N.D. ; Hon, Wing-Kai ; Lam, Tak-Wah ; Sung, Wing-Kin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c401t-1f4420c96f7df7fb0bd5b2902fef45095add20e46cf3452e64130041496e65ff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Algorithmics. Computability. Computer arithmetics</topic><topic>Applied sciences</topic><topic>Computer science; control theory; systems</topic><topic>Data processing. List processing. Character string processing</topic><topic>Exact sciences and technology</topic><topic>Memory organisation. Data processing</topic><topic>Software</topic><topic>Theoretical computing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Huynh, Trinh N.D.</creatorcontrib><creatorcontrib>Hon, Wing-Kai</creatorcontrib><creatorcontrib>Lam, Tak-Wah</creatorcontrib><creatorcontrib>Sung, Wing-Kin</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Theoretical computer science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Huynh, Trinh N.D.</au><au>Hon, Wing-Kai</au><au>Lam, Tak-Wah</au><au>Sung, Wing-Kin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Approximate string matching using compressed suffix arrays</atitle><jtitle>Theoretical computer science</jtitle><date>2006-03-07</date><risdate>2006</risdate><volume>352</volume><issue>1</issue><spage>240</spage><epage>249</epage><pages>240-249</pages><issn>0304-3975</issn><eissn>1879-2294</eissn><coden>TCSCDI</coden><abstract>Let
T
be a text of length
n
and
P
be a pattern of length
m
, both strings over a fixed finite alphabet
A
. The
k
-difference (
k
-mismatch, respectively) problem is to find all occurrences of
P
in
T
that have edit distance (Hamming distance, respectively) at most
k
from
P
. In this paper we investigate a well-studied case in which
T
is fixed and preprocessed into an indexing data structure so that any pattern query can be answered faster. We give a solution using an
O
(
n
log
n
)
bits indexing data structure with
O
(
|
A
|
k
m
k
·
max
(
k
,
log
n
)
+
occ
)
query time, where
occ
is the number of occurrences. The best previous result requires
O
(
n
log
n
)
bits indexing data structure and gives
O
(
|
A
|
k
m
k
+
2
+
occ
)
query time. Our solution also allows us to exploit compressed suffix arrays to reduce the indexing space to
O
(
n
)
bits, while increasing the query time by an
O
(
log
n
)
factor only.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.tcs.2005.11.022</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
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| ispartof | Theoretical computer science, 2006-03, Vol.352 (1), p.240-249 |
| issn | 0304-3975 1879-2294 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_28069572 |
| source | Access via ScienceDirect (Elsevier); EZB-FREE-00999 freely available EZB journals |
| subjects | Algorithmics. Computability. Computer arithmetics Applied sciences Computer science control theory systems Data processing. List processing. Character string processing Exact sciences and technology Memory organisation. Data processing Software Theoretical computing |
| title | Approximate string matching using compressed suffix arrays |
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