An O( n3) time algorithm for recognizing threshold dimension 2 graphs
Threshold dimension 2 graphs are the (edge-)intersection of two threshold graphs T 1 and T 2. Moreover they are the intersection graphs of points, axially parallel line segments and rectangles in the first quadrant of the Euclidean plane subject to the following constraints: 1. (1) line segments hav...
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Veröffentlicht in: | Information processing letters 1998-09, Vol.67 (5), p.255-259 |
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creator | Sterbini, Andrea Raschle, Thomas |
description | Threshold dimension 2 graphs are the (edge-)intersection of two threshold graphs
T
1 and
T
2. Moreover they are the intersection graphs of points, axially parallel line segments and rectangles in the first quadrant of the Euclidean plane subject to the following constraints:
1.
(1) line segments have one endpoint on one of the axes,
2.
(2) the lower left corner of each rectangle is the origin and
3.
(3) except for the above, every point, endpoint of a line segment and corner of a rectangle has unique
x and
y coordinates. Ma (1993) showed that the above geometrical representation called rectangle model can be constructed in
O(
n
3) time providing the vertices that correspond to the rectangles are known.
In this paper, we prove that there always exists a rectangle model in which the rectangles correspond to the vertices common to all maximum cliques. As the maximum cliques of a threshold dimension 2 graph can be found in
O(
n
3), the overall running time of our recognition algorithm is
O(
n
3), which compares favorably to the previous approaches with time complexity
O(
n
5) and
O(
n
4), respectively. |
doi_str_mv | 10.1016/S0020-0190(98)00112-4 |
format | Article |
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T
1 and
T
2. Moreover they are the intersection graphs of points, axially parallel line segments and rectangles in the first quadrant of the Euclidean plane subject to the following constraints:
1.
(1) line segments have one endpoint on one of the axes,
2.
(2) the lower left corner of each rectangle is the origin and
3.
(3) except for the above, every point, endpoint of a line segment and corner of a rectangle has unique
x and
y coordinates. Ma (1993) showed that the above geometrical representation called rectangle model can be constructed in
O(
n
3) time providing the vertices that correspond to the rectangles are known.
In this paper, we prove that there always exists a rectangle model in which the rectangles correspond to the vertices common to all maximum cliques. As the maximum cliques of a threshold dimension 2 graph can be found in
O(
n
3), the overall running time of our recognition algorithm is
O(
n
3), which compares favorably to the previous approaches with time complexity
O(
n
5) and
O(
n
4), respectively.</description><identifier>ISSN: 0020-0190</identifier><identifier>EISSN: 1872-6119</identifier><identifier>DOI: 10.1016/S0020-0190(98)00112-4</identifier><identifier>CODEN: IFPLAT</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Algorithmics. Computability. Computer arithmetics ; Algorithms ; Applied sciences ; Computer science; control theory; systems ; Exact sciences and technology ; Graphs ; Information processing ; Information retrieval. Graph ; Maximum cliques ; Studies ; Theoretical computing ; Threshold dimension 2 graphs</subject><ispartof>Information processing letters, 1998-09, Vol.67 (5), p.255-259</ispartof><rights>1998</rights><rights>1998 INIST-CNRS</rights><rights>Copyright Elsevier Sequoia S.A. Sep 15, 1998</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c460t-4ba3be4b1591488446fede391404490b231d77521a530c3e6845542bda08a66d3</citedby><cites>FETCH-LOGICAL-c460t-4ba3be4b1591488446fede391404490b231d77521a530c3e6845542bda08a66d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/S0020-0190(98)00112-4$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=2408702$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Sterbini, Andrea</creatorcontrib><creatorcontrib>Raschle, Thomas</creatorcontrib><title>An O( n3) time algorithm for recognizing threshold dimension 2 graphs</title><title>Information processing letters</title><description>Threshold dimension 2 graphs are the (edge-)intersection of two threshold graphs
T
1 and
T
2. Moreover they are the intersection graphs of points, axially parallel line segments and rectangles in the first quadrant of the Euclidean plane subject to the following constraints:
1.
(1) line segments have one endpoint on one of the axes,
2.
(2) the lower left corner of each rectangle is the origin and
3.
(3) except for the above, every point, endpoint of a line segment and corner of a rectangle has unique
x and
y coordinates. Ma (1993) showed that the above geometrical representation called rectangle model can be constructed in
O(
n
3) time providing the vertices that correspond to the rectangles are known.
In this paper, we prove that there always exists a rectangle model in which the rectangles correspond to the vertices common to all maximum cliques. As the maximum cliques of a threshold dimension 2 graph can be found in
O(
n
3), the overall running time of our recognition algorithm is
O(
n
3), which compares favorably to the previous approaches with time complexity
O(
n
5) and
O(
n
4), respectively.</description><subject>Algorithmics. Computability. Computer arithmetics</subject><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Graphs</subject><subject>Information processing</subject><subject>Information retrieval. Graph</subject><subject>Maximum cliques</subject><subject>Studies</subject><subject>Theoretical computing</subject><subject>Threshold dimension 2 graphs</subject><issn>0020-0190</issn><issn>1872-6119</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1998</creationdate><recordtype>article</recordtype><recordid>eNqFkMtKAzEUhoMoWC-PIAQR0cXoyWUymZUU8QaCC3UdMplMmzJNajIV9OlNbenCjavDge__z-FD6ITAFQEirl8BKBRAario5SUAIbTgO2hEZEULQUi9i0ZbZB8dpDQDAMFZNUJ3Y49fLrBnl3hwc4t1PwnRDdM57kLE0Zow8e7b-QkeptGmaehb3GbQJxc8pngS9WKajtBep_tkjzfzEL3f373dPhbPLw9Pt-PnwnABQ8EbzRrLG1LWhEvJuehsa1legPMaGspIW1UlJbpkYJgVkpclp02rQWohWnaIzte9ixg-ljYNau6SsX2vvQ3LpCitS1lTmcHTP-AsLKPPvynKKiqlAJKhcg2ZGFKKtlOL6OY6fikCamVW_ZpVK22qlurXrOI5d7Yp18novovaG5e2YcpBVkAzdrPGbDby6WxUyTjrjW1d9jqoNrh_Dv0ArtyJYA</recordid><startdate>19980915</startdate><enddate>19980915</enddate><creator>Sterbini, Andrea</creator><creator>Raschle, Thomas</creator><general>Elsevier B.V</general><general>Elsevier Science</general><general>Elsevier Sequoia S.A</general><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>19980915</creationdate><title>An O( n3) time algorithm for recognizing threshold dimension 2 graphs</title><author>Sterbini, Andrea ; Raschle, Thomas</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c460t-4ba3be4b1591488446fede391404490b231d77521a530c3e6845542bda08a66d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1998</creationdate><topic>Algorithmics. Computability. Computer arithmetics</topic><topic>Algorithms</topic><topic>Applied sciences</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Graphs</topic><topic>Information processing</topic><topic>Information retrieval. Graph</topic><topic>Maximum cliques</topic><topic>Studies</topic><topic>Theoretical computing</topic><topic>Threshold dimension 2 graphs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sterbini, Andrea</creatorcontrib><creatorcontrib>Raschle, Thomas</creatorcontrib><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>Information processing letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sterbini, Andrea</au><au>Raschle, Thomas</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An O( n3) time algorithm for recognizing threshold dimension 2 graphs</atitle><jtitle>Information processing letters</jtitle><date>1998-09-15</date><risdate>1998</risdate><volume>67</volume><issue>5</issue><spage>255</spage><epage>259</epage><pages>255-259</pages><issn>0020-0190</issn><eissn>1872-6119</eissn><coden>IFPLAT</coden><abstract>Threshold dimension 2 graphs are the (edge-)intersection of two threshold graphs
T
1 and
T
2. Moreover they are the intersection graphs of points, axially parallel line segments and rectangles in the first quadrant of the Euclidean plane subject to the following constraints:
1.
(1) line segments have one endpoint on one of the axes,
2.
(2) the lower left corner of each rectangle is the origin and
3.
(3) except for the above, every point, endpoint of a line segment and corner of a rectangle has unique
x and
y coordinates. Ma (1993) showed that the above geometrical representation called rectangle model can be constructed in
O(
n
3) time providing the vertices that correspond to the rectangles are known.
In this paper, we prove that there always exists a rectangle model in which the rectangles correspond to the vertices common to all maximum cliques. As the maximum cliques of a threshold dimension 2 graph can be found in
O(
n
3), the overall running time of our recognition algorithm is
O(
n
3), which compares favorably to the previous approaches with time complexity
O(
n
5) and
O(
n
4), respectively.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/S0020-0190(98)00112-4</doi><tpages>5</tpages></addata></record> |
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issn | 0020-0190 1872-6119 |
language | eng |
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source | Elsevier ScienceDirect Journals Complete |
subjects | Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Computer science control theory systems Exact sciences and technology Graphs Information processing Information retrieval. Graph Maximum cliques Studies Theoretical computing Threshold dimension 2 graphs |
title | An O( n3) time algorithm for recognizing threshold dimension 2 graphs |
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