{"id":"https://openalex.org/W2991108566","doi":"https://doi.org/10.1145/3365109.3368779","title":"HISDOM","display_name":"HISDOM","publication_year":2019,"publication_date":"2019-11-27","ids":{"openalex":"https://openalex.org/W2991108566","doi":"https://doi.org/10.1145/3365109.3368779","mag":"2991108566"},"language":"en","primary_location":{"id":"doi:10.1145/3365109.3368779","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3365109.3368779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies","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/A5100454231","display_name":"Jie Liu","orcid":"https://orcid.org/0000-0003-4955-8155"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Liu","raw_affiliation_strings":["Hohai University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026602746","display_name":"Yan Tang","orcid":"https://orcid.org/0000-0001-5239-5807"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Tang","raw_affiliation_strings":["Hohai University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101694146","display_name":"Xinyi Xu","orcid":"https://orcid.org/0000-0002-4776-2809"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyi Xu","raw_affiliation_strings":["Hohai University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I163340411"],"apc_list":null,"apc_paid":null,"fwci":0.2893,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68073152,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"67","last_page":"70"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9997000098228455,"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":0.9997000098228455,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9954000115394592,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/ontology","display_name":"Ontology","score":0.8111777305603027},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8103194832801819},{"id":"https://openalex.org/keywords/ontology-based-data-integration","display_name":"Ontology-based data integration","score":0.6101626753807068},{"id":"https://openalex.org/keywords/ontology-alignment","display_name":"Ontology alignment","score":0.5582134127616882},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5540826320648193},{"id":"https://openalex.org/keywords/upper-ontology","display_name":"Upper ontology","score":0.52439945936203},{"id":"https://openalex.org/keywords/suggested-upper-merged-ontology","display_name":"Suggested Upper Merged Ontology","score":0.5016815662384033},{"id":"https://openalex.org/keywords/process-ontology","display_name":"Process ontology","score":0.4998199939727783},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.48836323618888855},{"id":"https://openalex.org/keywords/semantic-integration","display_name":"Semantic integration","score":0.4783872365951538},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.43374723196029663},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4187876880168915},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28542545437812805},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.12747836112976074},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07056570053100586}],"concepts":[{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.8111777305603027},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8103194832801819},{"id":"https://openalex.org/C22550185","wikidata":"https://www.wikidata.org/wiki/Q7095047","display_name":"Ontology-based data integration","level":3,"score":0.6101626753807068},{"id":"https://openalex.org/C98893333","wikidata":"https://www.wikidata.org/wiki/Q4339878","display_name":"Ontology alignment","level":4,"score":0.5582134127616882},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5540826320648193},{"id":"https://openalex.org/C78726541","wikidata":"https://www.wikidata.org/wiki/Q3882785","display_name":"Upper ontology","level":3,"score":0.52439945936203},{"id":"https://openalex.org/C50971890","wikidata":"https://www.wikidata.org/wiki/Q7635093","display_name":"Suggested Upper Merged Ontology","level":4,"score":0.5016815662384033},{"id":"https://openalex.org/C137003198","wikidata":"https://www.wikidata.org/wiki/Q7247296","display_name":"Process ontology","level":3,"score":0.4998199939727783},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.48836323618888855},{"id":"https://openalex.org/C110903229","wikidata":"https://www.wikidata.org/wiki/Q7449064","display_name":"Semantic integration","level":4,"score":0.4783872365951538},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.43374723196029663},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4187876880168915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28542545437812805},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.12747836112976074},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07056570053100586},{"id":"https://openalex.org/C167379230","wikidata":"https://www.wikidata.org/wiki/Q1026884","display_name":"Semantic Web Stack","level":3,"score":0.0},{"id":"https://openalex.org/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3365109.3368779","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3365109.3368779","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6208365164","display_name":null,"funder_award_id":"2017YFC0405805","funder_id":"https://openalex.org/F4320335956","funder_display_name":"Key Technologies Research and Development Program of Guangzhou"}],"funders":[{"id":"https://openalex.org/F4320335956","display_name":"Key Technologies Research and Development Program of Guangzhou","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1558045115","https://openalex.org/W1720090307","https://openalex.org/W2024523516","https://openalex.org/W2102443632","https://openalex.org/W2131191620","https://openalex.org/W2385021243","https://openalex.org/W2534712034","https://openalex.org/W2903963001","https://openalex.org/W2911321769","https://openalex.org/W2962916648"],"related_works":["https://openalex.org/W2015306306","https://openalex.org/W2028429940","https://openalex.org/W2732632690","https://openalex.org/W2363188691","https://openalex.org/W2765352056","https://openalex.org/W2464347310","https://openalex.org/W2223008607","https://openalex.org/W2150375996","https://openalex.org/W269285493","https://openalex.org/W2384533895"],"abstract_inverted_index":{"In":[0],"the":[1,63,76,94,114,128,133,139,145,151,157,165,170,176,180,187,206,216,225],"information":[2,160],"explosion":[3],"era,":[4],"mapping":[5,33,56,60,65,81,88,134,204,217,227],"multiple":[6],"ontologies":[7,20],"in":[8,26,138,150,164,179,202],"different":[9,148],"knowledge":[10],"bases":[11],"could":[12,21],"provide":[13],"a":[14,54,85],"common":[15],"layer":[16],"from":[17],"which":[18],"several":[19,200],"be":[22,183],"accessed":[23],"and":[24,40,62,72,109,208,214],"exchanged":[25],"semantically":[27],"sound":[28],"manners.":[29],"However,":[30],"most":[31,47],"ontology":[32,64,80,87,98,153,181,203,226],"approaches":[34],"rely":[35],"heavily":[36],"on":[37,75,169],"human":[38],"annotation":[39],"are":[41,221],"restricted":[42],"to":[43,52,92,112,126,131,156],"limited":[44,51],"domains.":[45],"Moreover,":[46],"prior":[48],"work":[49],"is":[50,69,123,212],"combining":[53],"few":[55],"factors":[57,103,149,218],"with":[58],"moderate":[59],"accuracy,":[61],"weigh":[66],"calculation":[67],"process":[68,135],"not":[70],"adaptive":[71,209],"dynamic.":[73],"Based":[74],"current":[77],"generalization":[78,95],"of":[79,97,116,121,136,147,159,161,189,219],"methods,":[82],"we":[83],"propose":[84],"novel":[86],"system":[89],"called":[90],"HISDOM":[91,100,122,142,173,190,198,220],"improve":[93],"performance":[96,188],"mapping.":[99],"uses":[101],"comprehensive":[102],"like":[104],"concept":[105],"names,":[106],"attributes,":[107],"instances,":[108],"structural":[110],"similarities":[111],"determine":[113],"similarity":[115,130,154],"ontology.":[117,140,166],"A":[118],"key":[119],"novelty":[120],"leveraging":[124],"CNN":[125],"calculate":[127],"comment":[129],"assist":[132],"concepts":[137,178],"Then,":[141],"dynamically":[143],"derives":[144],"weight":[146],"overall":[152,171],"proportional":[155],"amount":[158],"each":[162],"factor":[163],"Finally,":[167],"based":[168],"similarity,":[172],"determines":[174],"whether":[175],"two":[177],"can":[182],"mapped.":[184],"We":[185],"study":[186],"through":[191],"extensive":[192],"experiments.":[193],"The":[194],"results":[195],"show":[196],"that":[197],"outperforms":[199],"baselines":[201],"tasks,":[205],"dynamic":[207],"weighting":[210],"mechanism":[211],"effective,":[213],"all":[215],"positive":[222],"towards":[223],"improving":[224],"accuracy.":[228]},"counts_by_year":[{"year":2022,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2019-12-05T00:00:00"}