iBet uBet
web content aggregator. Adding the entire web to your favor.
Link to original content:
https://api.openalex.org/works/doi:10.48550/ARXIV.2303.15465
{"id":"https://openalex.org/W4361230460","doi":"https://doi.org/10.48550/arxiv.2303.15465","title":"Exactly mergeable summaries","display_name":"Exactly mergeable summaries","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4361230460","doi":"https://doi.org/10.48550/arxiv.2303.15465"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2303.15465","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2303.15465","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001676164","display_name":"Vladimir Batagelj","orcid":"https://orcid.org/0000-0002-0240-9446"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Batagelj, Vladimir","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5001676164"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":70},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Trajectory Data Mining and Analysis","score":0.9425,"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":"Trajectory Data Mining and Analysis","score":0.9425,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.8770584},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.5107677},{"id":"https://openalex.org/keywords/clustering-algorithms","display_name":"Clustering Algorithms","score":0.491664},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.48056987}],"concepts":[{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.8770584},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.747139},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6840575},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5246332},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.5107677},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.48056987},{"id":"https://openalex.org/C2781311116","wikidata":"https://www.wikidata.org/wiki/Q83306","display_name":"Group (periodic table)","level":2,"score":0.47269037},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40133718},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39989313},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3141161},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25304595},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.22442773},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.11973718},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2303.15465","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2303.15465","pdf_url":"http://arxiv.org/pdf/2303.15465","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2303.15465","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2303.15465","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4389760904","https://openalex.org/W4323520239","https://openalex.org/W4306886878","https://openalex.org/W4242223894","https://openalex.org/W3148229873","https://openalex.org/W2366403280","https://openalex.org/W2150160875","https://openalex.org/W2091301346","https://openalex.org/W1517524280","https://openalex.org/W1495108544"],"abstract_inverted_index":{"In":[0,99,134],"the":[1,26,30,44,70,73,103,126],"analysis":[2,33,102],"of":[3,10,24,29,49,72,83,96,125,147,163,166],"large/big":[4],"data":[5,85,92,101],"sets,":[6],"aggregation":[7,37,51,59,127],"(replacing":[8],"values":[9,105],"a":[11,14,17,21,107,114,121,144],"variable":[12],"over":[13,106],"group":[15,109],"by":[16,89],"single":[18,122],"value)":[19],"is":[20,60,66],"standard":[22],"way":[23],"reducing":[25,69],"size":[27],"(complexity)":[28],"data.":[31,98],"Data":[32],"programs":[34],"provide":[35],"different":[36],"functions.":[38],"Recently":[39],"some":[40],"books":[41],"dealing":[42],"with":[43,57],"theoretical":[45,145],"and":[46,118,152],"algorithmic":[47],"background":[48,146],"traditional":[50,58],"functions":[52,128],"were":[53],"published.":[54],"A":[55,76],"problem":[56],"that":[61],"often":[62],"too":[63],"much":[64,77],"information":[65],"discarded":[67],"thus":[68],"precision":[71],"obtained":[74],"results.":[75],"better,":[78],"preserving":[79],"more":[80],"information,":[81],"summarization":[82],"original":[84],"can":[86],"be":[87],"achieved":[88],"representing":[90],"aggregated":[91,112],"using":[93],"selected":[94,108],"types":[95],"complex":[97,100,115,148],"measured":[104],"$A$":[110],"are":[111],"into":[113,120],"object":[116],"$\u03a3(A)$":[117],"not":[119,131],"value.":[123],"Most":[124],"theory":[129],"does":[130],"apply":[132],"directly.":[133],"our":[135],"contribution,":[136],"we":[137],"present":[138],"an":[139],"attempt":[140],"to":[141],"start":[142],"building":[143],"aggregation.":[149],"We":[150],"introduce":[151],"discuss":[153],"exactly":[154],"mergeable":[155],"summaries":[156],"for":[157,161,176],"which":[158],"it":[159],"holds":[160],"merging":[162],"disjoint":[164],"sets":[165],"units":[167],"\\[":[168],"\u03a3(A":[169],"\\cup":[170],"B)":[171],"=":[172,181],"F(":[173],"\u03a3(A),\u03a3(B)),\\qquad":[174],"\\mbox{":[175],"}":[177],"\\quad":[178],"A\\cap":[179],"B":[180],"\\emptyset":[182],".\\]":[183]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4361230460","counts_by_year":[],"updated_date":"2024-10-09T09:36:38.110927","created_date":"2023-03-31"}
