{"id":"https://openalex.org/W2139426900","doi":"https://doi.org/10.1145/1032222.1032253","title":"A novel improvement to the R*-tree spatial index using gain/loss metrics","display_name":"A novel improvement to the R*-tree spatial index using gain/loss metrics","publication_year":2004,"publication_date":"2004-11-12","ids":{"openalex":"https://openalex.org/W2139426900","doi":"https://doi.org/10.1145/1032222.1032253","mag":"2139426900"},"language":"en","primary_location":{"id":"doi:10.1145/1032222.1032253","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1032222.1032253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th annual ACM international workshop on Geographic information systems","raw_type":"proceedings-article"},"type":"article","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/A5100344040","display_name":"Donghui Zhang","orcid":"https://orcid.org/0000-0002-1690-4886"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Donghui Zhang","raw_affiliation_strings":["Northeastern University, Boston, MA","Northeastern University, Boston (MA)#TAB#"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"Northeastern University, Boston (MA)#TAB#","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101603608","display_name":"Tian Xia","orcid":"https://orcid.org/0000-0002-0053-9263"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Xia","raw_affiliation_strings":["Northeastern University, Boston, MA","Northeastern University, Boston (MA)#TAB#"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"Northeastern University, Boston (MA)#TAB#","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100344040"],"corresponding_institution_ids":["https://openalex.org/I12912129"],"apc_list":null,"apc_paid":null,"fwci":0.5609,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.68309783,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"204","last_page":"213"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9973000288009644,"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":0.9973000288009644,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9962999820709229,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9886999726295471,"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/index","display_name":"Index (typography)","score":0.5915697813034058},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5706804394721985},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5345315933227539},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3813689947128296},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3597983121871948},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2471759021282196},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.0928947925567627},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07767784595489502}],"concepts":[{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.5915697813034058},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5706804394721985},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5345315933227539},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3813689947128296},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3597983121871948},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2471759021282196},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0928947925567627},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07767784595489502}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1032222.1032253","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1032222.1032253","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th annual ACM international workshop on Geographic information systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1544850971","https://openalex.org/W2029306088","https://openalex.org/W2046441184","https://openalex.org/W2106642566","https://openalex.org/W2108900410","https://openalex.org/W2118269922","https://openalex.org/W2130566946","https://openalex.org/W2151135734","https://openalex.org/W4244513784"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857","https://openalex.org/W2350741829","https://openalex.org/W2530322880"],"abstract_inverted_index":{"The":[0,17,53,131,186],"R*-tree":[1,23,132],"is":[2,28,150],"a":[3,37,73,81,104,110,120,162,169,208,221],"state-of-the-art":[4],"spatial":[5],"index":[6],"structure.":[7],"It":[8],"has":[9],"already":[10],"found":[11],"its":[12],"way":[13],"into":[14,50,214,247],"commercial":[15],"systems.":[16],"most":[18],"important":[19],"improvement":[20],"of":[21,68,80,141,161,200,206],"the":[22,25,46,51,59,66,69,90,116,139,142,146,159,165,177,180,184,192,198,204,215,225,229,235,238,244,248],"over":[24],"original":[26],"R-tree":[27],"that":[29],"it":[30],"utilizes":[31],"forced":[32],"reinsertion.":[33],"That":[34],"is,":[35],"if":[36,95],"disk":[38],"page":[39,47],"overflows,":[40],"some":[41],"objects":[42,102,135],"are":[43,97,145,188],"removed":[44],"from":[45,103],"and":[48,62,106,164],"reinserted":[49],"index.":[52],"goals":[54],"are:":[55],"(a)":[56],"to":[57,64,72,88,100,138,167,175,182,219,223],"reduce":[58],"MBR":[60,70,144],"area;":[61],"(b)":[63],"keep":[65],"shape":[67],"close":[71],"square.":[74],"However,":[75,148],"no":[76],"existing":[77],"work":[78],"consists":[79],"unified":[82],"metric":[83],"which":[84,126],"can":[85,233],"be":[86],"used":[87],"balance":[89],"two":[91,98],"criteria.":[92],"For":[93],"example,":[94],"there":[96],"methods":[99],"remove":[101],"rectangle,":[105],"one":[107],"results":[108,118],"in":[109,119],"rectangle":[111,163],"with":[112,122,179,191,237],"smaller":[113],"area,":[114,125],"while":[115],"other":[117],"square":[121],"slightly":[123],"larger":[124],"method":[127],"shall":[128],"we":[129,156,172,202,217,232,242],"choose?":[130],"algorithm":[133],"selects":[134],"whose":[136],"distances":[137],"center":[140],"page's":[143],"largest.":[147],"this":[149,154],"not":[151],"optimal.":[152],"In":[153],"paper,":[155],"formally":[157],"define":[158,203],"<i>quality</i>":[160],"<i>gain</i>":[166],"shrink":[168,176],"rectangle.":[170,209],"Then":[171],"provide":[173],"algorithms":[174,187,246],"MBRs":[178],"goal":[181],"maximize":[183],"gain.":[185],"experimentally":[189],"compared":[190],"R*-tree's":[193],"reinsertion":[194],"algorithm.":[195],"Furthermore,":[196],"as":[197],"opposite":[199],"<i>gain</i>,":[201],"<i>loss</i>":[205],"expanding":[207],"While":[210],"inserting":[211],"an":[212],"object":[213,226],"R*-tree,":[216],"need":[218],"choose":[220,234],"sub-tree":[222,236],"put":[224],"in.":[227],"With":[228],"new":[230,245],"metric,":[231],"least":[239],"loss.":[240],"Finally,":[241],"integrate":[243],"R*-tree.":[249]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
