{"id":"https://openalex.org/W4409657537","doi":"https://doi.org/10.1145/3696410.3714947","title":"A Theory-Driven Approach to Inner Product Matrix Estimation for Incomplete Data: An Eigenvalue Perspective","display_name":"A Theory-Driven Approach to Inner Product Matrix Estimation for Incomplete Data: An Eigenvalue Perspective","publication_year":2025,"publication_date":"2025-04-22","ids":{"openalex":"https://openalex.org/W4409657537","doi":"https://doi.org/10.1145/3696410.3714947"},"language":"en","primary_location":{"id":"doi:10.1145/3696410.3714947","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714947","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714947","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","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/10.1145/3696410.3714947","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015454078","display_name":"Fangchen Yu","orcid":"https://orcid.org/0000-0002-1256-2719"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangchen Yu","raw_affiliation_strings":["The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-1256-2719","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yicheng Zeng","orcid":"https://orcid.org/0009-0009-3584-6368"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yicheng Zeng","raw_affiliation_strings":["Shenzhen International Center for Industrial and Applied Mathematics, Shenzhen Research Institute of Big Data, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0009-3584-6368","affiliations":[{"raw_affiliation_string":"Shenzhen International Center for Industrial and Applied Mathematics, Shenzhen Research Institute of Big Data, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210099586"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050195423","display_name":"Jianfeng Mao","orcid":"https://orcid.org/0000-0002-8969-0284"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Mao","raw_affiliation_strings":["The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China and Shenzhen Research Institute of Big Data, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-8969-0284","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China and Shenzhen Research Institute of Big Data, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924","https://openalex.org/I4210099586"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022112921","display_name":"Wenye Li","orcid":"https://orcid.org/0000-0002-5679-9670"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenye Li","raw_affiliation_strings":["The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-5679-9670","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.07530677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4077","last_page":"4088"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11476","display_name":"Graph theory and applications","score":0.9674000144004822,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6891115307807922},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.636389970779419},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5267571806907654},{"id":"https://openalex.org/keywords/matrix-algebra","display_name":"Matrix algebra","score":0.45759469270706177},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.4482670724391937},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.44663211703300476},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.41989952325820923},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36616358160972595},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3356721103191376},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3333612084388733},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.32991671562194824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24089699983596802},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12355253100395203},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11822393536567688},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.07293984293937683}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6891115307807922},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.636389970779419},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5267571806907654},{"id":"https://openalex.org/C2988995629","wikidata":"https://www.wikidata.org/wiki/Q2915729","display_name":"Matrix algebra","level":3,"score":0.45759469270706177},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.4482670724391937},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.44663211703300476},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.41989952325820923},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36616358160972595},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3356721103191376},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3333612084388733},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.32991671562194824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24089699983596802},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12355253100395203},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11822393536567688},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.07293984293937683},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3696410.3714947","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714947","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714947","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3696410.3714947","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3696410.3714947","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3696410.3714947","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM on Web Conference 2025","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G7273168071","display_name":null,"funder_award_id":"72394362","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8576010092","display_name":"\u57fa\u4e8e\u534f\u540c\u51b3\u7b56\u673a\u5236\u7684\u5177\u6709\u590d\u6742\u5ea6\u548c\u9c81\u68d2\u6027\u611f\u77e5\u7684\u591a\u673a\u56db\u7ef4\u822a\u8ff9\u89c4\u5212","funder_award_id":"U1733102","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322942","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48"},{"id":"https://openalex.org/F4320329174","display_name":"Shenzhen Municipal Science and Technology Innovation Council","ror":"https://ror.org/017n8df75"},{"id":"https://openalex.org/F4320331102","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89"},{"id":"https://openalex.org/F4320333998","display_name":"Shenzhen Research Institute, City University of Hong Kong","ror":"https://ror.org/00xc0ma20"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409657537.pdf","grobid_xml":"https://content.openalex.org/works/W4409657537.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W299839057","https://openalex.org/W1520752838","https://openalex.org/W2060581589","https://openalex.org/W2103972604","https://openalex.org/W2124608575","https://openalex.org/W2146731044","https://openalex.org/W2496114304","https://openalex.org/W2559655401","https://openalex.org/W2822791719","https://openalex.org/W2884552970","https://openalex.org/W2932881901","https://openalex.org/W2956143864","https://openalex.org/W2963975913","https://openalex.org/W2990138404","https://openalex.org/W2998108430","https://openalex.org/W3208503293","https://openalex.org/W3217140273","https://openalex.org/W4225362006","https://openalex.org/W4382237554","https://openalex.org/W4387171312","https://openalex.org/W4396758529","https://openalex.org/W4396758749"],"related_works":["https://openalex.org/W2165749285","https://openalex.org/W2576994247","https://openalex.org/W2062626603","https://openalex.org/W2608353378","https://openalex.org/W4249206767","https://openalex.org/W2474979212","https://openalex.org/W2562455930","https://openalex.org/W2001036795","https://openalex.org/W127450631","https://openalex.org/W2154748900"],"abstract_inverted_index":{"Addressing":[0],"the":[1,37,41,49,64,71],"critical":[2],"challenge":[3],"of":[4,40,73],"data":[5,83],"incompleteness":[6],"in":[7,89,103],"inner":[8,24,43,60,92],"product":[9,25,44,61,93],"matrix":[10,32,45],"estimation,":[11],"we":[12],"introduce":[13],"a":[14],"novel":[15],"eigenvalue":[16,38],"correction":[17],"method":[18,35,80],"designed":[19],"to":[20,46],"precisely":[21],"reconstruct":[22],"true":[23],"matrices":[26,62],"from":[27],"incomplete":[28,77,105],"data.":[29,78,106],"Utilizing":[30],"random":[31],"theory,":[33],"our":[34],"adjusts":[36],"distribution":[39],"estimated":[42],"align":[47],"with":[48],"ground":[50],"truth.":[51],"This":[52],"approach":[53],"significantly":[54],"reduces":[55],"estimation":[56],"errors":[57],"for":[58],"both":[59,90],"and":[63,85,95],"associated":[65],"Euclidean":[66],"distance":[67],"matrices,":[68],"thereby":[69],"enhancing":[70],"effectiveness":[72],"similarity":[74,86],"searches":[75],"on":[76],"Our":[79],"surpasses":[81],"traditional":[82],"imputation":[84],"calibration":[87],"techniques":[88],"maximum":[91],"search":[94,98],"nearest":[96],"neighbor":[97],"tasks,":[99],"demonstrating":[100],"marked":[101],"advancements":[102],"managing":[104]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}