{"id":"https://openalex.org/W2167932125","doi":"https://doi.org/10.1145/2676536.2676542","title":"Partitioning strategies for spatio-textual similarity join","display_name":"Partitioning strategies for spatio-textual similarity join","publication_year":2014,"publication_date":"2014-11-04","ids":{"openalex":"https://openalex.org/W2167932125","doi":"https://doi.org/10.1145/2676536.2676542","mag":"2167932125"},"language":"en","primary_location":{"id":"doi:10.1145/2676536.2676542","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2676536.2676542","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data","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/A5075728689","display_name":"Jinfeng Rao","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jinfeng Rao","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082997975","display_name":"Jimmy Lin","orcid":"https://orcid.org/0000-0002-0661-7189"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jimmy Lin","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087437068","display_name":"Hanan Samet","orcid":"https://orcid.org/0000-0001-8230-0653"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hanan Samet","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":1.2432,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.80402498,"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":"40","last_page":"49"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998999834060669,"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":0.9998999834060669,"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/T10757","display_name":"Geographic Information Systems Studies","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8142619132995605},{"id":"https://openalex.org/keywords/traverse","display_name":"Traverse","score":0.8111454248428345},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.7789338827133179},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6677547693252563},{"id":"https://openalex.org/keywords/join","display_name":"Join (topology)","score":0.6508368253707886},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.5810166001319885},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5681954026222229},{"id":"https://openalex.org/keywords/thread","display_name":"Thread (computing)","score":0.5222135782241821},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4936753213405609},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4703666865825653},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.44553709030151367},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.43637385964393616},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.4310585856437683},{"id":"https://openalex.org/keywords/edit-distance","display_name":"Edit distance","score":0.41651710867881775},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32825517654418945},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.2673259973526001},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21494251489639282},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11248862743377686},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08613258600234985}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8142619132995605},{"id":"https://openalex.org/C176809094","wikidata":"https://www.wikidata.org/wiki/Q15401496","display_name":"Traverse","level":2,"score":0.8111454248428345},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.7789338827133179},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6677547693252563},{"id":"https://openalex.org/C2776124973","wikidata":"https://www.wikidata.org/wiki/Q3183033","display_name":"Join (topology)","level":2,"score":0.6508368253707886},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.5810166001319885},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5681954026222229},{"id":"https://openalex.org/C138101251","wikidata":"https://www.wikidata.org/wiki/Q213092","display_name":"Thread (computing)","level":2,"score":0.5222135782241821},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4936753213405609},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4703666865825653},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.44553709030151367},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.43637385964393616},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.4310585856437683},{"id":"https://openalex.org/C44359876","wikidata":"https://www.wikidata.org/wiki/Q5338467","display_name":"Edit distance","level":2,"score":0.41651710867881775},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32825517654418945},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.2673259973526001},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21494251489639282},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11248862743377686},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08613258600234985},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2676536.2676542","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2676536.2676542","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.833.3576","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.833.3576","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://raojinfeng.com/publications/STJoin_SIGSPATIAL2014.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G727453110","display_name":null,"funder_award_id":"IIS-12-18043, IIS-10-18475, IIS-12-19023, IIS-13-20791","funder_id":"https://openalex.org/F4320337389","funder_display_name":"Division of Information and Intelligent Systems"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320337389","display_name":"Division of Information and Intelligent Systems","ror":"https://ror.org/053a2cp42"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1497953515","https://openalex.org/W1558961979","https://openalex.org/W1990111898","https://openalex.org/W1993997820","https://openalex.org/W1998157698","https://openalex.org/W2006307108","https://openalex.org/W2009899413","https://openalex.org/W2024678590","https://openalex.org/W2037562342","https://openalex.org/W2057002425","https://openalex.org/W2058903936","https://openalex.org/W2065259291","https://openalex.org/W2068902018","https://openalex.org/W2077765427","https://openalex.org/W2086985947","https://openalex.org/W2096598900","https://openalex.org/W2097184821","https://openalex.org/W2097776316","https://openalex.org/W2098994245","https://openalex.org/W2099568195","https://openalex.org/W2108009586","https://openalex.org/W2112129327","https://openalex.org/W2115500858","https://openalex.org/W2118269922","https://openalex.org/W2123060058","https://openalex.org/W2123171175","https://openalex.org/W2127675794","https://openalex.org/W2135503940","https://openalex.org/W2140048308","https://openalex.org/W2145349611","https://openalex.org/W2151135734","https://openalex.org/W2162006472","https://openalex.org/W2165735734","https://openalex.org/W2169307587","https://openalex.org/W2173213060","https://openalex.org/W6674576723"],"related_works":["https://openalex.org/W2377402383","https://openalex.org/W2380835401","https://openalex.org/W2381912691","https://openalex.org/W2350381577","https://openalex.org/W2353618196","https://openalex.org/W2348074676","https://openalex.org/W2385033175","https://openalex.org/W2374043190","https://openalex.org/W2363298784","https://openalex.org/W2367402697"],"abstract_inverted_index":{"Given":[0],"a":[1,72,80,98,130,142,163,204],"collection":[2],"of":[3,21,53,87,139,145,210],"geo-tagged":[4],"objects":[5,23],"with":[6,48,71],"associated":[7],"textual":[8,88,181],"descriptors,":[9],"the":[10,44,51,54,107,146,179],"spatio-textual":[11],"similarity":[12,182],"join":[13,45,183],"(STJoin)":[14],"problem":[15],"is":[16,32,40,46,68,95,150,203],"to":[17,50,69,96,110,152,160,166,175],"identify":[18],"all":[19],"pairs":[20,86],"similar":[22,85],"that":[24,126,200],"are":[25,135,196],"close":[26],"in":[27,34,129,137,170],"distance.":[28,115],"This":[29],"task,":[30],"which":[31,198],"useful":[33],"localized":[35],"recommendations":[36],"and":[37,78,105,124],"other":[38],"applications,":[39],"challenging":[41],"since":[42],"computing":[43],"super-linear":[47],"respect":[49],"size":[52],"collection.":[55],"In":[56,173],"this":[57],"paper,":[58],"we":[59,185],"explore":[60],"partitioning":[61],"strategies":[62],"for":[63,83],"tackling":[64],"STJoin.":[65],"One":[66],"approach":[67,94,149],"start":[70],"spatial":[73],"data":[74],"structure,":[75],"traverse":[76],"regions":[77],"apply":[79],"previous":[81],"algorithm":[82,109,190],"identifying":[84],"documents":[89],"called":[90],"All-Pairs.":[91],"An":[92],"alternative":[93],"construct":[97],"global":[99,147],"index":[100,148],"but":[101],"partition":[102],"postings":[103],"spatially":[104],"modify":[106],"All-Pairs":[108,177],"prune":[111],"candidates":[112],"based":[113],"on":[114,120],"We":[116],"evaluate":[117],"these":[118],"approaches":[119,134],"two":[121],"real-world":[122],"datasets":[123],"find":[125],"when":[127],"running":[128],"single":[131],"thread,":[132],"both":[133],"comparable":[136],"terms":[138],"performance.":[140],"However,":[141],"multi-threaded":[143],"implementation":[144],"able":[151],"achieve":[153],"far":[154],"better":[155],"speedup":[156],"given":[157],"its":[158],"ability":[159],"parallelize":[161],"at":[162],"finer":[164],"granularity":[165],"avoid":[167],"skewed":[168],"distributions":[169],"task":[171],"sizes.":[172],"addition":[174],"using":[176],"as":[178,192],"underlying":[180],"algorithm,":[184],"also":[186],"explored":[187],"an":[188],"alternate":[189],"known":[191],"PPJ:":[193],"our":[194],"findings":[195],"consistent,":[197],"suggests":[199],"load":[201],"balancing":[202],"fundamental":[205],"issue":[206],"affecting":[207],"parallel":[208],"implementations":[209],"STJoin":[211],"algorithms.":[212]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}
