{"id":"https://openalex.org/W2002817556","doi":"https://doi.org/10.1145/1866480.1866488","title":"An efficient features-based processing technique for supergraph queries","display_name":"An efficient features-based processing technique for supergraph queries","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2002817556","doi":"https://doi.org/10.1145/1866480.1866488","mag":"2002817556"},"language":"en","primary_location":{"id":"doi:10.1145/1866480.1866488","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1866480.1866488","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fourteenth International Database Engineering &amp; Applications Symposium on - IDEAS '10","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000296607","display_name":"Sherif Sakr","orcid":"https://orcid.org/0000-0002-2503-523X"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Sherif Sakr","raw_affiliation_strings":["University of New South Wales, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"University of New South Wales, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004537635","display_name":"Ghazi Al\u2010Naymat","orcid":"https://orcid.org/0000-0002-9661-5354"},"institutions":[{"id":"https://openalex.org/I1312486979","display_name":"Local Initiatives Support Corporation","ror":"https://ror.org/04r5g1376","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1312486979"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ghazi Al-Naymat","raw_affiliation_strings":["Cemagref - LISC, Aubiere Cedex, France","Cemagref - LISC, Aubiere Cedex, France#TAB#"],"affiliations":[{"raw_affiliation_string":"Cemagref - LISC, Aubiere Cedex, France","institution_ids":[]},{"raw_affiliation_string":"Cemagref - LISC, Aubiere Cedex, France#TAB#","institution_ids":["https://openalex.org/I1312486979"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000296607"],"corresponding_institution_ids":["https://openalex.org/I31746571"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09065434,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"42","last_page":"51"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/epigraph","display_name":"Epigraph","score":0.954858124256134},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8119970560073853},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45784372091293335},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08067798614501953},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.07624253630638123}],"concepts":[{"id":"https://openalex.org/C17192189","wikidata":"https://www.wikidata.org/wiki/Q1347059","display_name":"Epigraph","level":2,"score":0.954858124256134},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8119970560073853},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45784372091293335},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08067798614501953},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.07624253630638123}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1866480.1866488","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1866480.1866488","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fourteenth International Database Engineering &amp; Applications Symposium on - IDEAS '10","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.642.4019","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.642.4019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.nicta.com.au/pub?doc=4155","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W206244425","https://openalex.org/W1660390307","https://openalex.org/W1972243925","https://openalex.org/W1975068437","https://openalex.org/W1992363839","https://openalex.org/W2013497015","https://openalex.org/W2027943354","https://openalex.org/W2038386110","https://openalex.org/W2064744073","https://openalex.org/W2078202808","https://openalex.org/W2079499902","https://openalex.org/W2108150886","https://openalex.org/W2110034858","https://openalex.org/W2111036405","https://openalex.org/W2112776329","https://openalex.org/W2114414765","https://openalex.org/W2115051573","https://openalex.org/W2118995957","https://openalex.org/W2130426318","https://openalex.org/W2131323387","https://openalex.org/W2131374321","https://openalex.org/W2131485737","https://openalex.org/W2134356404","https://openalex.org/W2136593687","https://openalex.org/W2139242647","https://openalex.org/W2142965177","https://openalex.org/W2145631416","https://openalex.org/W2147913014","https://openalex.org/W2152609228","https://openalex.org/W2166205117","https://openalex.org/W2169310183","https://openalex.org/W2170726034"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2355558294","https://openalex.org/W2392366684","https://openalex.org/W2381998515","https://openalex.org/W2393671386","https://openalex.org/W2377617670","https://openalex.org/W2713931874","https://openalex.org/W3164236790","https://openalex.org/W2361142453"],"abstract_inverted_index":{"Graphs":[0],"are":[1,81,102],"widely":[2],"used":[3],"for":[4],"modeling":[5],"complicated":[6],"data":[7,201],"such":[8],"as":[9],"social":[10],"networks,":[11],"chemical":[12],"compounds,":[13],"protein":[14],"interactions,":[15],"XML":[16],"documents":[17],"and":[18,27,133,162,182,199,207],"multimedia":[19],"databases.":[20],"To":[21],"be":[22,113],"able":[23],"to":[24,112,149,173,203],"effectively":[25],"understand":[26],"utilize":[28],"any":[29,119],"collection":[30],"of":[31,51,67,93,100,118,129,144,154,165,178,186,195,210],"graphs,":[32],"a":[33,60,68],"graph":[34,52,61,94,120,131,170,180],"database":[35,62,121],"that":[36,97],"efficiently":[37],"supports":[38],"elementary":[39],"querying":[40],"mechanisms":[41],"is":[42,47,72,96,110,123],"crucially":[43],"required.":[44],"Supergraph":[45],"query":[46,70,134,187],"an":[48,151,160,192],"important":[49],"type":[50],"queries":[53,95],"which":[54,80],"has":[55],"many":[56],"practical":[57],"applications.":[58],"Given":[59],"D,":[63],"the":[64,91,116,127,130,142,146,175,184,205,208],"answer":[65],"set":[66,194],"supergraph":[69,155],"q":[71],"computed":[73],"by":[74],"retrieving":[75],"all":[76],"graphs":[77,101],"in":[78,84,89],"D":[79],"fully":[82],"contained":[83],"q.":[85],"A":[86],"primary":[87],"challenge":[88],"computing":[90],"answers":[92],"pair-wise":[98,179],"comparisons":[99,181],"usually":[103],"hard":[104],"problems.":[105],"For":[106],"example,":[107],"subgraph":[108],"isomorphism":[109],"known":[111],"NP-complete.":[114],"Clearly,":[115],"success":[117],"application":[122],"directly":[124],"dependent":[125],"on":[126,159,197],"efficiency":[128,185,206],"indexing":[132],"processing":[135],"mechanisms.":[136],"In":[137],"this":[138],"paper,":[139],"we":[140,190],"study":[141],"problem":[143],"using":[145],"relational":[147],"infrastructure":[148],"achieve":[150],"efficient":[152,163],"evaluation":[153],"queries.":[156],"We":[157],"rely":[158],"effective":[161],"layer":[164],"features-based":[166],"summary":[167],"structures,":[168],"called":[169],"features":[171],"knowledge,":[172],"reduce":[174],"required":[176],"number":[177],"boost":[183],"processing.":[188],"Finally,":[189],"conduct":[191],"extensive":[193],"experiments":[196],"real":[198],"synthetic":[200],"sets":[202],"demonstrate":[204],"scalability":[209],"our":[211],"approach.":[212]},"counts_by_year":[],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
