{"id":"https://openalex.org/W4414230208","doi":"https://doi.org/10.1109/tpami.2025.3610211","title":"Efficient Nearest Neighbor Search Using Dynamic Programming","display_name":"Efficient Nearest Neighbor Search Using Dynamic Programming","publication_year":2025,"publication_date":"2025-09-16","ids":{"openalex":"https://openalex.org/W4414230208","doi":"https://doi.org/10.1109/tpami.2025.3610211","pmid":"https://pubmed.ncbi.nlm.nih.gov/40956692"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3610211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3610211","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5079619510","display_name":"Pengfei Wang","orcid":"https://orcid.org/0000-0002-2079-275X"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Wang","raw_affiliation_strings":["School of Computer Science and Technology, Shandong University, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0002-2079-275X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong University, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiantao Song","orcid":"https://orcid.org/0009-0007-0907-3731"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiantao Song","raw_affiliation_strings":["School of Computer Science and Technology, Shandong University, Qingdao, China"],"raw_orcid":"https://orcid.org/0009-0007-0907-3731","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong University, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062030077","display_name":"Shiqing Xin","orcid":"https://orcid.org/0000-0001-8452-8723"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiqing Xin","raw_affiliation_strings":["School of Computer Science and Technology, Shandong University, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0001-8452-8723","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong University, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049236113","display_name":"Shuangmin Chen","orcid":"https://orcid.org/0000-0002-0835-3316"},"institutions":[{"id":"https://openalex.org/I143413998","display_name":"Qingdao University of Science and Technology","ror":"https://ror.org/041j8js14","country_code":"CN","type":"education","lineage":["https://openalex.org/I143413998"]},{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuangmin Chen","raw_affiliation_strings":["School of Information and Technology, China","School of Information and Technology, Qingdao University of Science and Technology, Shandong, China"],"raw_orcid":"https://orcid.org/0000-0002-0835-3316","affiliations":[{"raw_affiliation_string":"School of Information and Technology, China","institution_ids":["https://openalex.org/I75689368"]},{"raw_affiliation_string":"School of Information and Technology, Qingdao University of Science and Technology, Shandong, China","institution_ids":["https://openalex.org/I143413998"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087472282","display_name":"Changhe Tu","orcid":"https://orcid.org/0000-0002-1231-3392"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changhe Tu","raw_affiliation_strings":["School of Computer Science and Technology, Shandong University, Qingdao, China"],"raw_orcid":"https://orcid.org/0000-0002-1231-3392","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong University, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100668416","display_name":"Wenping Wang","orcid":"https://orcid.org/0000-0002-2284-3952"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wenping Wang","raw_affiliation_strings":["Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA","Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-2284-3952","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089852302","display_name":"Jiaye Wang","orcid":"https://orcid.org/0009-0006-0132-2492"},"institutions":[{"id":"https://openalex.org/I80143920","display_name":"Shandong University of Science and Technology","ror":"https://ror.org/04gtjhw98","country_code":"CN","type":"education","lineage":["https://openalex.org/I80143920"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaye Wang","raw_affiliation_strings":["School of Computer Science and Technology, Shandong University, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Shandong University, Qingdao, China","institution_ids":["https://openalex.org/I80143920"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.624,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.9079296,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"48","issue":"1","first_page":"999","last_page":"1014"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9670000076293945,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9670000076293945,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9465000033378601,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9144999980926514,"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/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.7437999844551086},{"id":"https://openalex.org/keywords/voronoi-diagram","display_name":"Voronoi diagram","score":0.7064999938011169},{"id":"https://openalex.org/keywords/nearest-neighbor-graph","display_name":"Nearest neighbor graph","score":0.6295999884605408},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.6150000095367432},{"id":"https://openalex.org/keywords/cover-tree","display_name":"Cover tree","score":0.5532000064849854},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.5291000008583069},{"id":"https://openalex.org/keywords/fixed-radius-near-neighbors","display_name":"Fixed-radius near neighbors","score":0.4893999993801117},{"id":"https://openalex.org/keywords/large-margin-nearest-neighbor","display_name":"Large margin nearest neighbor","score":0.4675000011920929},{"id":"https://openalex.org/keywords/dynamic-programming","display_name":"Dynamic programming","score":0.46470001339912415},{"id":"https://openalex.org/keywords/best-bin-first","display_name":"Best bin first","score":0.4587000012397766}],"concepts":[{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.7437999844551086},{"id":"https://openalex.org/C24881265","wikidata":"https://www.wikidata.org/wiki/Q757267","display_name":"Voronoi diagram","level":2,"score":0.7064999938011169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6517999768257141},{"id":"https://openalex.org/C90988772","wikidata":"https://www.wikidata.org/wiki/Q2855103","display_name":"Nearest neighbor graph","level":3,"score":0.6295999884605408},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.6150000095367432},{"id":"https://openalex.org/C53661774","wikidata":"https://www.wikidata.org/wiki/Q13108095","display_name":"Cover tree","level":5,"score":0.5532000064849854},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.5291000008583069},{"id":"https://openalex.org/C46264003","wikidata":"https://www.wikidata.org/wiki/Q5456333","display_name":"Fixed-radius near neighbors","level":5,"score":0.4893999993801117},{"id":"https://openalex.org/C94475309","wikidata":"https://www.wikidata.org/wiki/Q6489154","display_name":"Large margin nearest neighbor","level":3,"score":0.4675000011920929},{"id":"https://openalex.org/C37404715","wikidata":"https://www.wikidata.org/wiki/Q380679","display_name":"Dynamic programming","level":2,"score":0.46470001339912415},{"id":"https://openalex.org/C161986146","wikidata":"https://www.wikidata.org/wiki/Q4896845","display_name":"Best bin first","level":3,"score":0.4587000012397766},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.45010000467300415},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4438000023365021},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.44040000438690186},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4339999854564667},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.42250001430511475},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4047999978065491},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4047999978065491},{"id":"https://openalex.org/C13670688","wikidata":"https://www.wikidata.org/wiki/Q3500548","display_name":"Space partitioning","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.36070001125335693},{"id":"https://openalex.org/C102164700","wikidata":"https://www.wikidata.org/wiki/Q17162702","display_name":"Nearest-neighbor chain algorithm","level":5,"score":0.3368000090122223},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32499998807907104},{"id":"https://openalex.org/C74197172","wikidata":"https://www.wikidata.org/wiki/Q1195339","display_name":"Directed acyclic graph","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3095000088214874},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C29123130","wikidata":"https://www.wikidata.org/wiki/Q874709","display_name":"Computational geometry","level":2,"score":0.3052999973297119},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3025999963283539},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28790000081062317},{"id":"https://openalex.org/C115908005","wikidata":"https://www.wikidata.org/wiki/Q2668364","display_name":"Combinatorial explosion","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C168781493","wikidata":"https://www.wikidata.org/wiki/Q80585","display_name":"Associative array","level":2,"score":0.26840001344680786},{"id":"https://openalex.org/C106278948","wikidata":"https://www.wikidata.org/wiki/Q1198051","display_name":"R-tree","level":4,"score":0.2583000063896179},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3610211","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3610211","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:40956692","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40956692","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4846070451","display_name":null,"funder_award_id":"62272277","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7015702209","display_name":null,"funder_award_id":"U23A20312","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W21857574","https://openalex.org/W2024668293","https://openalex.org/W2046053182","https://openalex.org/W2049981393","https://openalex.org/W2050252966","https://openalex.org/W2051200663","https://openalex.org/W2086504823","https://openalex.org/W2092065474","https://openalex.org/W2109991971","https://openalex.org/W2118269922","https://openalex.org/W2141245797","https://openalex.org/W2152864241","https://openalex.org/W2155166664","https://openalex.org/W2165489143","https://openalex.org/W2165558283","https://openalex.org/W2165835468","https://openalex.org/W2167853719","https://openalex.org/W2294798173","https://openalex.org/W2566265240","https://openalex.org/W2581716810","https://openalex.org/W2773349014","https://openalex.org/W2810310533","https://openalex.org/W2972931660","https://openalex.org/W2997027240","https://openalex.org/W3169028576","https://openalex.org/W3174637788","https://openalex.org/W3197903162","https://openalex.org/W4214494916","https://openalex.org/W4310924423","https://openalex.org/W4311805700","https://openalex.org/W4376456786","https://openalex.org/W4383534265","https://openalex.org/W4384661698","https://openalex.org/W4385288719","https://openalex.org/W4405873576"],"related_works":[],"abstract_inverted_index":{"Given":[0],"a":[1,43,56,63,105,172,186],"collection":[2],"of":[3,90,94,108,150,189,218],"points":[4,36,40,167],"in":[5,117,127,168,178],"$\\mathbb":[6],"{R}^{3}$R3,":[7],"KD-Tree":[8],"and":[9,23,142,215],"R-Tree":[10],"are":[11],"well-known":[12],"nearest":[13,161],"neighbor":[14,162],"search":[15],"(NNS)":[16],"algorithms":[17],"that":[18,61,101,174],"rely":[19],"on":[20],"spatial":[21],"partitioning":[22],"indexing":[24],"techniques.":[25],"However,":[26],"when":[27],"the":[28,34,38,70,78,82,87,91,95,160,164,169,212],"query":[29,47],"point":[30,170],"is":[31,153],"far":[32],"from":[33],"data":[35,39,74,96],"or":[37],"inherently":[41],"represent":[42],"2-manifold":[44],"surface,":[45],"their":[46],"performance":[48],"may":[49],"degrade.":[50],"To":[51],"address":[52],"this,":[53],"we":[54],"propose":[55],"novel":[57],"dynamic":[58],"programming":[59],"technique":[60],"precomputes":[62],"Directed":[64],"Acyclic":[65],"Graph":[66],"(DAG)":[67],"to":[68,157],"encode":[69],"proximity":[71,83],"structure":[72,84],"between":[73],"points.":[75,97],"More":[76],"specifically,":[77],"DAG":[79],"captures":[80],"how":[81],"evolves":[85],"during":[86],"incremental":[88,191],"construction":[89,192],"Voronoi":[92],"diagram":[93],"Experimental":[98],"results":[99,207],"demonstrate":[100],"our":[102,111,151,190,194,219],"method":[103,195],"achieves":[104],"speed":[106],"increase":[107],"1-10x.":[109],"Furthermore,":[110],"algorithm":[112],"demonstrates":[113],"significant":[114],"practical":[115,216],"value":[116],"diverse":[118],"applications.":[119],"We":[120],"validated":[121],"its":[122,154],"effectiveness":[123],"through":[124],"extensive":[125],"testing":[126],"four":[128],"key":[129],"applications:":[130],"Point-to-Mesh":[131],"Distance":[132,144],"Queries,":[133],"Iterative":[134],"Closest":[135],"Point":[136],"(ICP)":[137],"Registration,":[138],"Density":[139,182],"Peak":[140,183],"Clustering,":[141],"Point-to-Segments":[143],"Queries.":[145],"A":[146],"particularly":[147],"notable":[148],"feature":[149],"approach":[152],"unique":[155],"ability":[156],"efficiently":[158],"identify":[159],"among":[163],"first":[165],"$k$k":[166],"cloud,":[171],"capability":[173],"enables":[175],"substantial":[176],"acceleration":[177],"low-dimensional":[179],"applications":[180],"like":[181],"Clustering.":[184],"As":[185],"natural":[187],"extension":[188],"process,":[193],"can":[196],"also":[197],"be":[198],"readily":[199],"adapted":[200],"for":[201],"farthest-point":[202],"sampling":[203],"tasks.":[204],"These":[205],"experimental":[206],"across":[208],"multiple":[209],"domains":[210],"underscore":[211],"broad":[213],"applicability":[214],"importance":[217],"approach.":[220]},"counts_by_year":[{"year":2026,"cited_by_count":4}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}