{"id":"https://openalex.org/W4416250631","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227903","title":"NCMI: A Framework for Missing Modality Generation in Multi-modal Recommendation","display_name":"NCMI: A Framework for Missing Modality Generation in Multi-modal Recommendation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250631","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227903"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5045411027","display_name":"Ning Wu","orcid":"https://orcid.org/0000-0002-1899-2648"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ningyu Wu","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences),School of Mathematics and Statistics,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences),School of Mathematics and Statistics,Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100633825","display_name":"Lin Cai","orcid":"https://orcid.org/0000-0003-0903-6731"},"institutions":[{"id":"https://openalex.org/I152269853","display_name":"Qilu University of Technology","ror":"https://ror.org/04hyzq608","country_code":"CN","type":"education","lineage":["https://openalex.org/I152269853"]},{"id":"https://openalex.org/I4210142748","display_name":"Shandong Academy of Sciences","ror":"https://ror.org/04y8d6y55","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lilin Cai","raw_affiliation_strings":["Qilu University of Technology (Shandong Academy of Sciences),School of Mathematics and Statistics,Jinan,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Qilu University of Technology (Shandong Academy of Sciences),School of Mathematics and Statistics,Jinan,China","institution_ids":["https://openalex.org/I152269853","https://openalex.org/I4210142748"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.8579000234603882,"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"}},"topics":[{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.8579000234603882,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.02370000071823597,"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":0.01940000057220459,"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/modality","display_name":"Modality (human\u2013computer interaction)","score":0.6891000270843506},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.6888999938964844},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5468999743461609},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.374099999666214},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.36469998955726624},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.36070001125335693},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.32749998569488525}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7663000226020813},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.6891000270843506},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.6888999938964844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6345000267028809},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5468999743461609},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44190001487731934},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3822999894618988},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.374099999666214},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.36469998955726624},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35429999232292175},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.32409998774528503},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2935999929904938},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2524000108242035}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227903","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2027731328","https://openalex.org/W2145360759","https://openalex.org/W2194775991","https://openalex.org/W2480680997","https://openalex.org/W2605280356","https://openalex.org/W2963655167","https://openalex.org/W2963683654","https://openalex.org/W2966501701","https://openalex.org/W2970641574","https://openalex.org/W2982108874","https://openalex.org/W3093002391","https://openalex.org/W3178419880","https://openalex.org/W3192113933","https://openalex.org/W4284687944","https://openalex.org/W4292092796","https://openalex.org/W4312583258","https://openalex.org/W4312824836","https://openalex.org/W4321593910","https://openalex.org/W4322718576","https://openalex.org/W4372260527","https://openalex.org/W4387968671","https://openalex.org/W4392366685","https://openalex.org/W4396736086","https://openalex.org/W4399114772","https://openalex.org/W4400526287","https://openalex.org/W4402404329","https://openalex.org/W4403282582","https://openalex.org/W4403582878","https://openalex.org/W4403791453","https://openalex.org/W4404352050","https://openalex.org/W4408146479"],"related_works":[],"abstract_inverted_index":{"When":[0],"specific":[1],"modalities":[2,104],"of":[3,20,97,105,114],"items":[4,67],"are":[5],"randomly":[6],"missing,":[7],"traditional":[8],"multi-modal":[9,184],"recommendation":[10,29,138,162],"methods":[11,174],"may":[12],"fail":[13],"to":[14,24,64,73,81,120,182],"fully":[15],"capture":[16],"the":[17,74,79,102,106,112,115,122,131,137,145,156],"intrinsic":[18],"characteristics":[19],"these":[21],"items,":[22],"leading":[23],"a":[25,37,55,89],"significant":[26],"degradation":[27],"in":[28,175],"performance.":[30,163],"To":[31],"address":[32],"this":[33],"challenge,":[34],"we":[35,53,87,129],"propose":[36],"novel":[38],"missing":[39,116,132,157,177],"modality":[40,70,92,117,133],"generation":[41,113,134],"framework":[42],"based":[43,59],"on":[44,60,148,165],"Neighbors":[45],"and":[46,118],"Cross":[47],"Modality":[48],"Invariant":[49],"Features":[50],"(NCMI).":[51],"First,":[52],"introduce":[54],"neighbor":[56],"selection":[57],"mechanism":[58],"collaborative":[61],"interaction":[62],"frequencies":[63],"identify":[65],"neighboring":[66],"with":[68,136],"similar":[69],"preference":[71],"features":[72,100,110,153],"incomplete":[75,107],"item.":[76,108],"This":[77],"allows":[78],"generator":[80],"obtain":[82],"effective":[83],"intra-modality":[84],"information.":[85],"Next,":[86],"design":[88],"pre-trained":[90],"cross":[91],"invariant":[93,99],"feature":[94],"extractor":[95],"capable":[96],"extracting":[98],"from":[101],"available":[103],"These":[109],"guide":[111],"help":[119],"bridge":[121],"semantic":[123,152],"gaps":[124],"across":[125],"heterogeneous":[126],"modalities.":[127],"Finally,":[128],"integrate":[130],"process":[135],"task":[139],"through":[140],"joint":[141],"optimization,":[142],"ensuring":[143],"that":[144,170],"model":[146],"focuses":[147],"recovering":[149],"preference-related":[150],"high-order":[151],"when":[154],"generating":[155],"modality,":[158],"thus":[159],"further":[160],"improving":[161],"Experiments":[164],"real":[166],"world":[167],"datasets":[168],"show":[169],"NCMI":[171],"outperforms":[172],"existing":[173],"handling":[176],"modalities,":[178],"highlighting":[179],"its":[180],"potential":[181],"improve":[183],"recommendations.":[185]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}