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...
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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 |
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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> |
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issn | 0004-5411 1557-735X |
language | eng |
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source | ACM Digital Library Complete |
subjects | Algorithms Approximation Combinatorial analysis Pattern matching Strings |
title | Approximating Edit Distance in Truly Subquadratic Time: Quantum and MapReduce |
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