{"id":"https://openalex.org/W4381327902","doi":"https://doi.org/10.1145/3593078.3593932","title":"Learned Spatial Data Partitioning","display_name":"Learned Spatial Data Partitioning","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4381327902","doi":"https://doi.org/10.1145/3593078.3593932"},"language":"en","primary_location":{"id":"doi:10.1145/3593078.3593932","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3593078.3593932","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3593078.3593932","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management","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/10.1145/3593078.3593932","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000480088","display_name":"Keizo Hori","orcid":"https://orcid.org/0009-0002-3336-329X"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Keizo Hori","raw_affiliation_strings":["Osaka University, Suita, Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041703913","display_name":"Yuya Sasaki","orcid":"https://orcid.org/0000-0002-8548-3181"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuya Sasaki","raw_affiliation_strings":["Osaka University, Suita, Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009228302","display_name":"Daichi Amagata","orcid":"https://orcid.org/0000-0001-8571-4931"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daichi Amagata","raw_affiliation_strings":["Osaka University, Suita, Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092212221","display_name":"Yuki Murosaki","orcid":"https://orcid.org/0009-0002-8178-5227"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yuki Murosaki","raw_affiliation_strings":["Osaka University, Suita, Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030272842","display_name":"Makoto Onizuka","orcid":"https://orcid.org/0000-0001-5559-8300"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Makoto Onizuka","raw_affiliation_strings":["Osaka University, Suita, Japan"],"affiliations":[{"raw_affiliation_string":"Osaka University, Suita, Japan","institution_ids":["https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5000480088"],"corresponding_institution_ids":["https://openalex.org/I98285908"],"apc_list":null,"apc_paid":null,"fwci":0.9905,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75040298,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9995999932289124,"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":0.9995999932289124,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9940000176429749,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9891999959945679,"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":0.8539711833000183},{"id":"https://openalex.org/keywords/space-partitioning","display_name":"Space partitioning","score":0.6896194219589233},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.6518413424491882},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5899991989135742},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.5750961303710938},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5520157217979431},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.551544725894928},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.5416197776794434},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47763243317604065},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46436282992362976},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4182506203651428},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.18185043334960938}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8539711833000183},{"id":"https://openalex.org/C13670688","wikidata":"https://www.wikidata.org/wiki/Q3500548","display_name":"Space partitioning","level":2,"score":0.6896194219589233},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.6518413424491882},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5899991989135742},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.5750961303710938},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5520157217979431},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.551544725894928},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.5416197776794434},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47763243317604065},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46436282992362976},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4182506203651428},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.18185043334960938},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3593078.3593932","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3593078.3593932","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3593078.3593932","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3593078.3593932","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3593078.3593932","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3593078.3593932","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1069223013","display_name":null,"funder_award_id":"JSPS KAKENHI","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G3459562248","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4227499671","display_name":null,"funder_award_id":"KAKENHI Grant","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4636223006","display_name":null,"funder_award_id":"JSPS KAK","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G4827429566","display_name":null,"funder_award_id":"Grant Numbers","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G5057850187","display_name":null,"funder_award_id":"JP22H03700","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G5786340949","display_name":null,"funder_award_id":"KAKENHI Grant Number","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G6789972089","display_name":null,"funder_award_id":"JP20H00584","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G7299757773","display_name":"User-Attracted Low-Delay MaaS Infrastructure for Solving Social Problems in Society 5.0","funder_award_id":"20H00584","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8430481527","display_name":null,"funder_award_id":"Number","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"},{"id":"https://openalex.org/G8438910869","display_name":null,"funder_award_id":"22H03700","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4381327902.pdf","grobid_xml":"https://content.openalex.org/works/W4381327902.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W32403112","https://openalex.org/W41554520","https://openalex.org/W2008196645","https://openalex.org/W2066799613","https://openalex.org/W2115583184","https://openalex.org/W2197411628","https://openalex.org/W2280230190","https://openalex.org/W2436533802","https://openalex.org/W2548613432","https://openalex.org/W2788862220","https://openalex.org/W2809148419","https://openalex.org/W2896720518","https://openalex.org/W2949830935","https://openalex.org/W2965426524","https://openalex.org/W3029327553","https://openalex.org/W3029564598","https://openalex.org/W3094011786","https://openalex.org/W3106489949","https://openalex.org/W3109597879","https://openalex.org/W3214190608","https://openalex.org/W3215621605","https://openalex.org/W4206776951","https://openalex.org/W4210494128"],"related_works":["https://openalex.org/W3148227991","https://openalex.org/W1486593826","https://openalex.org/W2771174107","https://openalex.org/W1536965844","https://openalex.org/W2344941099","https://openalex.org/W4322212724","https://openalex.org/W2106788855","https://openalex.org/W3081561710","https://openalex.org/W2477413883","https://openalex.org/W2463773089"],"abstract_inverted_index":{"Due":[0],"to":[1,14,20,43,88,124],"the":[2,6,61,118],"significant":[3],"increase":[4],"in":[5,60],"size":[7],"of":[8,39,48,63,79],"spatial":[9,23,32,41,57,80,102],"data,":[10,103],"it":[11],"is":[12],"essential":[13],"use":[15],"distributed":[16],"parallel":[17],"processing":[18],"systems":[19],"efficiently":[21,108],"analyze":[22],"data.":[24],"In":[25],"this":[26],"paper,":[27],"we":[28],"first":[29],"study":[30],"learned":[31],"data":[33,42,49,58,81],"partitioning,":[34],"which":[35,96],"effectively":[36],"assigns":[37],"groups":[38],"big":[40],"computers":[44],"based":[45],"on":[46],"locations":[47],"by":[50,122],"using":[51],"machine":[52],"learning":[53,65,72,75,86],"techniques.":[54],"We":[55],"formalize":[56],"partitioning":[59,82],"context":[62],"reinforcement":[64,71],"and":[66,83,100,116],"develop":[67],"a":[68],"novel":[69],"deep":[70],"algorithm.":[73],"Our":[74,93],"algorithm":[76],"leverages":[77],"features":[78],"prunes":[84],"ineffective":[85],"processes":[87],"find":[89],"optimal":[90],"partitions":[91,110],"efficiently.":[92],"experimental":[94],"study,":[95],"uses":[97],"Apache":[98],"Sedona":[99],"real-world":[101],"demonstrates":[104],"that":[105],"our":[106],"method":[107],"finds":[109],"for":[111],"accelerating":[112],"distance":[113],"join":[114],"queries":[115],"reduces":[117],"workload":[119],"run":[120],"time":[121],"up":[123],"59.4%.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}