{"id":"https://openalex.org/W4411015369","doi":"https://doi.org/10.1145/3728725.3728740","title":"Multimodal Knowledge Graph Inference Method Based on Cross-Attention Mechanism","display_name":"Multimodal Knowledge Graph Inference Method Based on Cross-Attention Mechanism","publication_year":2025,"publication_date":"2025-02-21","ids":{"openalex":"https://openalex.org/W4411015369","doi":"https://doi.org/10.1145/3728725.3728740"},"language":"en","primary_location":{"id":"doi:10.1145/3728725.3728740","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728740","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728740","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728740","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zijian Han","orcid":"https://orcid.org/0009-0007-7876-5141"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zijian Han","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University, Harbin, Heilongjiang, China"],"raw_orcid":"https://orcid.org/0009-0007-7876-5141","affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, Heilongjiang, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"last","author":{"id":null,"display_name":"Changbo Hou","orcid":"https://orcid.org/0009-0003-5603-3223"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changbo Hou","raw_affiliation_strings":["College of Information and Communication Engineering, Harbin Engineering University, Harbin, Heilongjiang, China"],"raw_orcid":"https://orcid.org/0009-0003-5603-3223","affiliations":[{"raw_affiliation_string":"College of Information and Communication Engineering, Harbin Engineering University, Harbin, Heilongjiang, China","institution_ids":["https://openalex.org/I151727225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05290966,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"94","last_page":"100"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","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/T11273","display_name":"Advanced Graph Neural Networks","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/T10028","display_name":"Topic Modeling","score":0.9897000193595886,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9882000088691711,"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/computer-science","display_name":"Computer science","score":0.7792693376541138},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6904897689819336},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5733304023742676},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5074207186698914},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47342875599861145},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43569445610046387},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.4225514233112335},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4036102592945099},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33977606892585754},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1197151243686676},{"id":"https://openalex.org/keywords/epistemology","display_name":"Epistemology","score":0.062461256980895996}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7792693376541138},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6904897689819336},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5733304023742676},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5074207186698914},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47342875599861145},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43569445610046387},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.4225514233112335},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4036102592945099},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33977606892585754},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1197151243686676},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.062461256980895996},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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:10.1145/3728725.3728740","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728740","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728740","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3728725.3728740","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3728725.3728740","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3728725.3728740","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 2nd International Conference on Generative Artificial Intelligence and Information Security","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411015369.pdf","grobid_xml":"https://content.openalex.org/works/W4411015369.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W2807480793"],"related_works":["https://openalex.org/W2382997850","https://openalex.org/W2390968135","https://openalex.org/W2382213751","https://openalex.org/W2351750670","https://openalex.org/W1597848696","https://openalex.org/W2354715126","https://openalex.org/W2388563748","https://openalex.org/W2375179084","https://openalex.org/W2366646518","https://openalex.org/W2370906336"],"abstract_inverted_index":{"Existing":[0],"multimodal":[1,16,46,167],"knowledge":[2,47,92,168],"graph":[3,48,82,169],"reasoning":[4,49],"methods":[5],"often":[6],"rely":[7],"on":[8,52,132,150],"simple":[9],"weighted":[10],"averaging":[11],"or":[12],"attention":[13,73,83],"mechanisms":[14],"for":[15],"feature":[17,116],"fusion,":[18],"which":[19],"frequently":[20],"results":[21,139],"in":[22,166],"the":[23,33,59,87,91,122,125,133,142],"loss":[24],"of":[25,90,124],"modality-specific":[26],"information":[27,89],"and":[28,79,107,135,159,164],"fails":[29],"to":[30,62,75,85,101,113],"fully":[31],"exploit":[32],"complementary":[34],"relationships":[35],"between":[36,105],"modalities.":[37,119],"To":[38,120],"address":[39],"these":[40],"issues,":[41],"this":[42],"paper":[43],"proposes":[44],"a":[45,53,67,71,81,95,108],"method":[50],"based":[51],"cross-attention":[54,109],"mechanism.":[55],"The":[56,138],"model":[57,61,69,144],"employs":[58],"BERT":[60],"encode":[63,76],"textual":[64],"information,":[65,78],"introduces":[66],"VGG-16":[68],"with":[70],"multi-scale":[72],"module":[74],"visual":[77],"utilizes":[80],"mechanism":[84,110],"extract":[86],"structural":[88],"graph.":[93],"Additionally,":[94],"contrastive":[96],"learning":[97],"framework":[98],"is":[99,111],"introduced":[100],"reduce":[102],"semantic":[103],"inconsistencies":[104],"modalities,":[106],"used":[112],"achieve":[114],"dynamic":[115],"fusion":[117],"across":[118],"validate":[121],"effectiveness":[123,163],"proposed":[126,143],"model,":[127],"comparative":[128],"experiments":[129],"were":[130],"conducted":[131],"FB15k-237":[134],"DB15K":[136],"datasets.":[137],"show":[140],"that":[141],"significantly":[145],"outperforms":[146],"existing":[147],"benchmark":[148],"models":[149],"key":[151],"evaluation":[152],"metrics":[153],"such":[154],"as":[155],"MRR,":[156],"Hit@1,":[157],"Hit@3,":[158],"Hit@10,":[160],"demonstrating":[161],"its":[162],"robustness":[165],"reasoning.":[170]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
