{"id":"https://openalex.org/W1997210240","doi":"https://doi.org/10.1177/0165551512463650","title":"Backward inference and pruning for RDF change detection using RDBMS","display_name":"Backward inference and pruning for RDF change detection using RDBMS","publication_year":2012,"publication_date":"2012-11-28","ids":{"openalex":"https://openalex.org/W1997210240","doi":"https://doi.org/10.1177/0165551512463650","mag":"1997210240"},"language":"en","primary_location":{"id":"doi:10.1177/0165551512463650","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0165551512463650","pdf_url":null,"source":{"id":"https://openalex.org/S68913162","display_name":"Journal of Information Science","issn_l":"0165-5515","issn":["0165-5515","1741-6485"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information Science","raw_type":"journal-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/A5011064699","display_name":"Dong-Hyuk Im","orcid":"https://orcid.org/0000-0002-0290-755X"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong-Hyuk Im","raw_affiliation_strings":["School of Computer Science and Engineering, Seoul National University, Seoul, Korea","School of Computer Science and Engineering, Seoul National, University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Seoul National, University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100360920","display_name":"Sangwon Lee","orcid":"https://orcid.org/0000-0003-3936-9342"},"institutions":[{"id":"https://openalex.org/I848706","display_name":"Sungkyunkwan University","ror":"https://ror.org/04q78tk20","country_code":"KR","type":"education","lineage":["https://openalex.org/I848706"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sang-Won Lee","raw_affiliation_strings":["School of Information and Communication Engineering, Sungkyunkwan University, Suwon, Korea","School of Information & Communication Engineering Sungkyunkwan University, Suwon, Korea#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Sungkyunkwan University, Suwon, Korea","institution_ids":["https://openalex.org/I848706"]},{"raw_affiliation_string":"School of Information & Communication Engineering Sungkyunkwan University, Suwon, Korea#TAB#","institution_ids":["https://openalex.org/I848706"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102980943","display_name":"Hyoung-Joo Kim","orcid":"https://orcid.org/0000-0003-2574-720X"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyoung-Joo Kim","raw_affiliation_strings":["School of Computer Science and Engineering, Seoul National University, Seoul, Korea","School of Computer Science and Engineering, Seoul National, University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Seoul National, University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0446,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.91395308,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"39","issue":"2","first_page":"238","last_page":"255"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11719","display_name":"Data Quality and Management","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/rdf","display_name":"RDF","score":0.7912214994430542},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7746168375015259},{"id":"https://openalex.org/keywords/sparql","display_name":"SPARQL","score":0.6217820048332214},{"id":"https://openalex.org/keywords/cwm","display_name":"Cwm","score":0.6211819052696228},{"id":"https://openalex.org/keywords/rdf/xml","display_name":"RDF/XML","score":0.6202979683876038},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5762255191802979},{"id":"https://openalex.org/keywords/linked-data","display_name":"Linked data","score":0.5703483819961548},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5662209391593933},{"id":"https://openalex.org/keywords/rdf-schema","display_name":"RDF Schema","score":0.536891520023346},{"id":"https://openalex.org/keywords/backward-chaining","display_name":"Backward chaining","score":0.49904870986938477},{"id":"https://openalex.org/keywords/chaining","display_name":"Chaining","score":0.4948202967643738},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36322659254074097},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.3017553687095642},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.23502898216247559},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.19694414734840393},{"id":"https://openalex.org/keywords/inference-engine","display_name":"Inference engine","score":0.19559332728385925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1729426383972168}],"concepts":[{"id":"https://openalex.org/C147497476","wikidata":"https://www.wikidata.org/wiki/Q54872","display_name":"RDF","level":3,"score":0.7912214994430542},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7746168375015259},{"id":"https://openalex.org/C41009113","wikidata":"https://www.wikidata.org/wiki/Q54871","display_name":"SPARQL","level":4,"score":0.6217820048332214},{"id":"https://openalex.org/C157595922","wikidata":"https://www.wikidata.org/wiki/Q50745537","display_name":"Cwm","level":5,"score":0.6211819052696228},{"id":"https://openalex.org/C78923513","wikidata":"https://www.wikidata.org/wiki/Q2115","display_name":"RDF/XML","level":5,"score":0.6202979683876038},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5762255191802979},{"id":"https://openalex.org/C69075417","wikidata":"https://www.wikidata.org/wiki/Q515701","display_name":"Linked data","level":3,"score":0.5703483819961548},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5662209391593933},{"id":"https://openalex.org/C15657843","wikidata":"https://www.wikidata.org/wiki/Q1751819","display_name":"RDF Schema","level":5,"score":0.536891520023346},{"id":"https://openalex.org/C129916263","wikidata":"https://www.wikidata.org/wiki/Q1141183","display_name":"Backward chaining","level":4,"score":0.49904870986938477},{"id":"https://openalex.org/C49020025","wikidata":"https://www.wikidata.org/wiki/Q1059099","display_name":"Chaining","level":2,"score":0.4948202967643738},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36322659254074097},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3017553687095642},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.23502898216247559},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.19694414734840393},{"id":"https://openalex.org/C46743427","wikidata":"https://www.wikidata.org/wiki/Q1341685","display_name":"Inference engine","level":3,"score":0.19559332728385925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1729426383972168},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1177/0165551512463650","is_oa":false,"landing_page_url":"https://doi.org/10.1177/0165551512463650","pdf_url":null,"source":{"id":"https://openalex.org/S68913162","display_name":"Journal of Information Science","issn_l":"0165-5515","issn":["0165-5515","1741-6485"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320017","host_organization_name":"SAGE Publishing","host_organization_lineage":["https://openalex.org/P4310320017"],"host_organization_lineage_names":["SAGE Publishing"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Information Science","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W29172951","https://openalex.org/W162603549","https://openalex.org/W167120483","https://openalex.org/W1479991530","https://openalex.org/W1489843519","https://openalex.org/W1504439773","https://openalex.org/W1560455220","https://openalex.org/W1562378842","https://openalex.org/W1583014304","https://openalex.org/W1652544960","https://openalex.org/W1812636409","https://openalex.org/W1818528352","https://openalex.org/W1844586300","https://openalex.org/W1845680681","https://openalex.org/W1952297973","https://openalex.org/W1971563190","https://openalex.org/W1974505664","https://openalex.org/W1980056392","https://openalex.org/W2020490061","https://openalex.org/W2026446368","https://openalex.org/W2084962311","https://openalex.org/W2094112778","https://openalex.org/W2096578078","https://openalex.org/W2101491706","https://openalex.org/W2103779611","https://openalex.org/W2116587674","https://openalex.org/W2140613126","https://openalex.org/W2148853245","https://openalex.org/W2152593687","https://openalex.org/W2154496576","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W43613300","https://openalex.org/W4301152651","https://openalex.org/W3095079208","https://openalex.org/W2602535883","https://openalex.org/W1495140256","https://openalex.org/W1506173319","https://openalex.org/W2506264631","https://openalex.org/W60849243","https://openalex.org/W1479991530","https://openalex.org/W2363387259"],"abstract_inverted_index":{"Recent":[0],"studies":[1],"on":[2,10,79,97],"change":[3,70,105,183],"detection":[4,71,184],"for":[5,73,109,181],"RDF":[6,24,50,60,74,112,142,182],"data":[7,61,113,143],"have":[8,34],"focused":[9],"minimizing":[11],"the":[12,21,28,31,40,45,49,52,89,94,98,119,129,132,150,171,176],"delta":[13,29,120],"size":[14],"and,":[15],"as":[16],"a":[17,68],"way":[18],"to":[19,58,116,128,140,147,170],"exploit":[20],"semantics":[22],"of":[23,48,87,158,178],"models":[25],"in":[26,138,149,168],"reducing":[27],"size,":[30],"forward-chaining":[32,41,134],"inferences":[33,42],"been":[35],"widely":[36],"employed.":[37],"However,":[38],"since":[39],"should":[43],"pre-compute":[44],"entire":[46],"closure":[47,96],"model,":[51],"existing":[53,133,172],"approaches":[54],"are":[55],"not":[56],"scalable":[57,69,104],"large":[59,146],"sets.":[62],"In":[63,107,136],"this":[64],"paper,":[65],"we":[66,153],"propose":[67],"scheme":[72,124],"data,":[75],"which":[76],"is":[77,125],"based":[78],"backward-chaining":[80],"inference":[81,179],"and":[82,103],"pruning.":[83],"Our":[84,161],"scheme,":[85,167],"instead":[86],"pre-computing":[88],"full":[90],"closure,":[91],"computes":[92],"only":[93],"necessary":[95],"fly,":[99],"thus":[100],"achieving":[101],"fast":[102],"detection.":[106],"addition,":[108,137],"any":[110],"two":[111],"input":[114],"files":[115],"be":[117],"compared,":[118],"obtained":[121],"from":[122,131],"our":[123,159,166],"always":[126],"equivalent":[127],"one":[130],"inferences.":[135],"order":[139],"handle":[141],"sets":[144],"too":[145],"fit":[148],"available":[151],"RAM,":[152],"present":[154],"an":[155],"SQL-based":[156],"implementation":[157],"scheme.":[160],"experimental":[162],"results":[163],"show":[164],"that":[165],"comparison":[169],"schemes,":[173],"can":[174],"reduce":[175],"number":[177],"triples":[180],"by":[185],"10\u201360%.":[186]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
