Approximating Edit Distance in Truly Subquadratic Time: Quantum and MapReduce

The edit distance between two strings is defined as the smallest number of insertions , deletions , and substitutions that need to be made to transform one of the strings to another one. Approximating edit distance in subquadratic time is “one of the biggest unsolved problems in the field of combina...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of the ACM 2021-06, Vol.68 (3), p.1-41
Hauptverfasser: Boroujeni, Mahdi, Ehsani, Soheil, Ghodsi, Mohammad, Hajiaghayi, Mohammadtaghi, Seddighin, Saeed
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 41
container_issue 3
container_start_page 1
container_title Journal of the ACM
container_volume 68
creator Boroujeni, Mahdi
Ehsani, Soheil
Ghodsi, Mohammad
Hajiaghayi, Mohammadtaghi
Seddighin, Saeed
description The edit distance between two strings is defined as the smallest number of insertions , deletions , and substitutions that need to be made to transform one of the strings to another one. Approximating edit distance in subquadratic time is “one of the biggest unsolved problems in the field of combinatorial pattern matching” [37]. Our main result is a quantum constant approximation algorithm for computing the edit distance in truly subquadratic time. More precisely, we give an quantum algorithm that approximates the edit distance within a factor of 3. We further extend this result to an quantum algorithm that approximates the edit distance within a larger constant factor. Our solutions are based on a framework for approximating edit distance in parallel settings. This framework requires as black box an algorithm that computes the distances of several smaller strings all at once. For a quantum algorithm, we reduce the black box to metric estimation and provide efficient algorithms for approximating it. We further show that this framework enables us to approximate edit distance in distributed settings. To this end, we provide a MapReduce algorithm to approximate edit distance within a factor of , with sublinearly many machines and sublinear memory. Also, our algorithm runs in a logarithmic number of rounds.
doi_str_mv 10.1145/3456807
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2538398739</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2538398739</sourcerecordid><originalsourceid>FETCH-LOGICAL-c286t-c51249fd63bda664f391aa5a6888e0c093fd23f812cf267a99927e750e35ded83</originalsourceid><addsrcrecordid>eNotkMtKAzEUhoMoOFbxFQIuXI3mMrm5K7VeoEXUEdwNaS6S0s5MkwnYt3ekXR0OfPz_OR8A1xjdYVyxe1oxLpE4AQVmTJSCsu9TUCCEqpJVGJ-Di5TW44oIEgVYTvs-dr9hq4fQ_sC5DQN8DGnQrXEwtLCOebOHn3m1y9rGETKwDlv3AN-zboe8hbq1cKn7D2ezcZfgzOtNclfHOQFfT_N69lIu3p5fZ9NFaYjkQ2kYJpXyltOV1ZxXniqsNdNcSumQQYp6S6iXmBhPuNBKKSKcYMhRZp2VdAJuDrnj7bvs0tCsuxzbsbIhjEqqpKBqpG4PlIldStH5po_jo3HfYNT8u2qOrugfGeZaMw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2538398739</pqid></control><display><type>article</type><title>Approximating Edit Distance in Truly Subquadratic Time: Quantum and MapReduce</title><source>ACM Digital Library Complete</source><creator>Boroujeni, Mahdi ; Ehsani, Soheil ; Ghodsi, Mohammad ; Hajiaghayi, Mohammadtaghi ; Seddighin, Saeed</creator><creatorcontrib>Boroujeni, Mahdi ; Ehsani, Soheil ; Ghodsi, Mohammad ; Hajiaghayi, Mohammadtaghi ; Seddighin, Saeed</creatorcontrib><description>The edit distance between two strings is defined as the smallest number of insertions , deletions , and substitutions that need to be made to transform one of the strings to another one. Approximating edit distance in subquadratic time is “one of the biggest unsolved problems in the field of combinatorial pattern matching” [37]. Our main result is a quantum constant approximation algorithm for computing the edit distance in truly subquadratic time. More precisely, we give an quantum algorithm that approximates the edit distance within a factor of 3. We further extend this result to an quantum algorithm that approximates the edit distance within a larger constant factor. Our solutions are based on a framework for approximating edit distance in parallel settings. This framework requires as black box an algorithm that computes the distances of several smaller strings all at once. For a quantum algorithm, we reduce the black box to metric estimation and provide efficient algorithms for approximating it. We further show that this framework enables us to approximate edit distance in distributed settings. To this end, we provide a MapReduce algorithm to approximate edit distance within a factor of , with sublinearly many machines and sublinear memory. Also, our algorithm runs in a logarithmic number of rounds.</description><identifier>ISSN: 0004-5411</identifier><identifier>EISSN: 1557-735X</identifier><identifier>DOI: 10.1145/3456807</identifier><language>eng</language><publisher>New York: Association for Computing Machinery</publisher><subject>Algorithms ; Approximation ; Combinatorial analysis ; Pattern matching ; Strings</subject><ispartof>Journal of the ACM, 2021-06, Vol.68 (3), p.1-41</ispartof><rights>Copyright Association for Computing Machinery May 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c286t-c51249fd63bda664f391aa5a6888e0c093fd23f812cf267a99927e750e35ded83</citedby><cites>FETCH-LOGICAL-c286t-c51249fd63bda664f391aa5a6888e0c093fd23f812cf267a99927e750e35ded83</cites><orcidid>0000-0001-7246-251X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Boroujeni, Mahdi</creatorcontrib><creatorcontrib>Ehsani, Soheil</creatorcontrib><creatorcontrib>Ghodsi, Mohammad</creatorcontrib><creatorcontrib>Hajiaghayi, Mohammadtaghi</creatorcontrib><creatorcontrib>Seddighin, Saeed</creatorcontrib><title>Approximating Edit Distance in Truly Subquadratic Time: Quantum and MapReduce</title><title>Journal of the ACM</title><description>The edit distance between two strings is defined as the smallest number of insertions , deletions , and substitutions that need to be made to transform one of the strings to another one. Approximating edit distance in subquadratic time is “one of the biggest unsolved problems in the field of combinatorial pattern matching” [37]. Our main result is a quantum constant approximation algorithm for computing the edit distance in truly subquadratic time. More precisely, we give an quantum algorithm that approximates the edit distance within a factor of 3. We further extend this result to an quantum algorithm that approximates the edit distance within a larger constant factor. Our solutions are based on a framework for approximating edit distance in parallel settings. This framework requires as black box an algorithm that computes the distances of several smaller strings all at once. For a quantum algorithm, we reduce the black box to metric estimation and provide efficient algorithms for approximating it. We further show that this framework enables us to approximate edit distance in distributed settings. To this end, we provide a MapReduce algorithm to approximate edit distance within a factor of , with sublinearly many machines and sublinear memory. Also, our algorithm runs in a logarithmic number of rounds.</description><subject>Algorithms</subject><subject>Approximation</subject><subject>Combinatorial analysis</subject><subject>Pattern matching</subject><subject>Strings</subject><issn>0004-5411</issn><issn>1557-735X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNotkMtKAzEUhoMoOFbxFQIuXI3mMrm5K7VeoEXUEdwNaS6S0s5MkwnYt3ekXR0OfPz_OR8A1xjdYVyxe1oxLpE4AQVmTJSCsu9TUCCEqpJVGJ-Di5TW44oIEgVYTvs-dr9hq4fQ_sC5DQN8DGnQrXEwtLCOebOHn3m1y9rGETKwDlv3AN-zboe8hbq1cKn7D2ezcZfgzOtNclfHOQFfT_N69lIu3p5fZ9NFaYjkQ2kYJpXyltOV1ZxXniqsNdNcSumQQYp6S6iXmBhPuNBKKSKcYMhRZp2VdAJuDrnj7bvs0tCsuxzbsbIhjEqqpKBqpG4PlIldStH5po_jo3HfYNT8u2qOrugfGeZaMw</recordid><startdate>20210601</startdate><enddate>20210601</enddate><creator>Boroujeni, Mahdi</creator><creator>Ehsani, Soheil</creator><creator>Ghodsi, Mohammad</creator><creator>Hajiaghayi, Mohammadtaghi</creator><creator>Seddighin, Saeed</creator><general>Association for Computing Machinery</general><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><orcidid>https://orcid.org/0000-0001-7246-251X</orcidid></search><sort><creationdate>20210601</creationdate><title>Approximating Edit Distance in Truly Subquadratic Time: Quantum and MapReduce</title><author>Boroujeni, Mahdi ; Ehsani, Soheil ; Ghodsi, Mohammad ; Hajiaghayi, Mohammadtaghi ; Seddighin, Saeed</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c286t-c51249fd63bda664f391aa5a6888e0c093fd23f812cf267a99927e750e35ded83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Approximation</topic><topic>Combinatorial analysis</topic><topic>Pattern matching</topic><topic>Strings</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Boroujeni, Mahdi</creatorcontrib><creatorcontrib>Ehsani, Soheil</creatorcontrib><creatorcontrib>Ghodsi, Mohammad</creatorcontrib><creatorcontrib>Hajiaghayi, Mohammadtaghi</creatorcontrib><creatorcontrib>Seddighin, Saeed</creatorcontrib><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>Journal of the ACM</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Boroujeni, Mahdi</au><au>Ehsani, Soheil</au><au>Ghodsi, Mohammad</au><au>Hajiaghayi, Mohammadtaghi</au><au>Seddighin, Saeed</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Approximating Edit Distance in Truly Subquadratic Time: Quantum and MapReduce</atitle><jtitle>Journal of the ACM</jtitle><date>2021-06-01</date><risdate>2021</risdate><volume>68</volume><issue>3</issue><spage>1</spage><epage>41</epage><pages>1-41</pages><issn>0004-5411</issn><eissn>1557-735X</eissn><abstract>The edit distance between two strings is defined as the smallest number of insertions , deletions , and substitutions that need to be made to transform one of the strings to another one. Approximating edit distance in subquadratic time is “one of the biggest unsolved problems in the field of combinatorial pattern matching” [37]. Our main result is a quantum constant approximation algorithm for computing the edit distance in truly subquadratic time. More precisely, we give an quantum algorithm that approximates the edit distance within a factor of 3. We further extend this result to an quantum algorithm that approximates the edit distance within a larger constant factor. Our solutions are based on a framework for approximating edit distance in parallel settings. This framework requires as black box an algorithm that computes the distances of several smaller strings all at once. For a quantum algorithm, we reduce the black box to metric estimation and provide efficient algorithms for approximating it. We further show that this framework enables us to approximate edit distance in distributed settings. To this end, we provide a MapReduce algorithm to approximate edit distance within a factor of , with sublinearly many machines and sublinear memory. Also, our algorithm runs in a logarithmic number of rounds.</abstract><cop>New York</cop><pub>Association for Computing Machinery</pub><doi>10.1145/3456807</doi><tpages>41</tpages><orcidid>https://orcid.org/0000-0001-7246-251X</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0004-5411
ispartof Journal of the ACM, 2021-06, Vol.68 (3), p.1-41
issn 0004-5411
1557-735X
language eng
recordid cdi_proquest_journals_2538398739
source ACM Digital Library Complete
subjects Algorithms
Approximation
Combinatorial analysis
Pattern matching
Strings
title Approximating Edit Distance in Truly Subquadratic Time: Quantum and MapReduce
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T14%3A23%3A27IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Approximating%20Edit%20Distance%20in%20Truly%20Subquadratic%20Time:%20Quantum%20and%20MapReduce&rft.jtitle=Journal%20of%20the%20ACM&rft.au=Boroujeni,%20Mahdi&rft.date=2021-06-01&rft.volume=68&rft.issue=3&rft.spage=1&rft.epage=41&rft.pages=1-41&rft.issn=0004-5411&rft.eissn=1557-735X&rft_id=info:doi/10.1145/3456807&rft_dat=%3Cproquest_cross%3E2538398739%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2538398739&rft_id=info:pmid/&rfr_iscdi=true