{"id":"https://openalex.org/W2151249511","doi":"https://doi.org/10.1145/2684822.2685297","title":"Optimal Space-time Tradeoffs for Inverted Indexes","display_name":"Optimal Space-time Tradeoffs for Inverted Indexes","publication_year":2015,"publication_date":"2015-01-28","ids":{"openalex":"https://openalex.org/W2151249511","doi":"https://doi.org/10.1145/2684822.2685297","mag":"2151249511"},"language":"en","primary_location":{"id":"doi:10.1145/2684822.2685297","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2684822.2685297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth ACM International Conference on Web Search and Data Mining","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/A5003288532","display_name":"Giuseppe Ottaviano","orcid":"https://orcid.org/0000-0003-1191-8258"},"institutions":[{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giuseppe Ottaviano","raw_affiliation_strings":["National Research Council of Italy, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Research Council of Italy, Pisa, Italy","institution_ids":["https://openalex.org/I4210155236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018894843","display_name":"Nicola Tonellotto","orcid":"https://orcid.org/0000-0002-7427-1001"},"institutions":[{"id":"https://openalex.org/I4210155236","display_name":"National Research Council","ror":"https://ror.org/04zaypm56","country_code":"IT","type":"nonprofit","lineage":["https://openalex.org/I4210155236"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicola Tonellotto","raw_affiliation_strings":["National Research Council of Italy, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Research Council of Italy, Pisa, Italy","institution_ids":["https://openalex.org/I4210155236"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084138015","display_name":"Rossano Venturini","orcid":"https://orcid.org/0000-0002-9830-3936"},"institutions":[{"id":"https://openalex.org/I108290504","display_name":"University of Pisa","ror":"https://ror.org/03ad39j10","country_code":"IT","type":"education","lineage":["https://openalex.org/I108290504"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Rossano Venturini","raw_affiliation_strings":["Department of Computer Science, University of Pisa, Pisa, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Pisa, Pisa, Italy","institution_ids":["https://openalex.org/I108290504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"47","last_page":"56"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9998000264167786,"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9988999962806702,"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/encoder","display_name":"Encoder","score":0.8713529109954834},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6290209293365479},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6262226104736328},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5816264152526855},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5747399926185608},{"id":"https://openalex.org/keywords/linear-space","display_name":"Linear space","score":0.5608524084091187},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.5490739941596985},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5484628081321716},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5174685120582581},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4910545349121094},{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.4105568826198578},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3655298948287964},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.32760170102119446},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.308963418006897},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.1317492425441742},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.12894409894943237},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.11277714371681213}],"concepts":[{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.8713529109954834},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6290209293365479},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6262226104736328},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5816264152526855},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5747399926185608},{"id":"https://openalex.org/C176370821","wikidata":"https://www.wikidata.org/wiki/Q1826459","display_name":"Linear space","level":2,"score":0.5608524084091187},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.5490739941596985},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5484628081321716},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5174685120582581},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4910545349121094},{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.4105568826198578},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3655298948287964},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.32760170102119446},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.308963418006897},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.1317492425441742},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.12894409894943237},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.11277714371681213},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2684822.2685297","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2684822.2685297","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arpi.unipi.it:11568/753935","is_oa":false,"landing_page_url":"http://hdl.handle.net/11568/753935","pdf_url":null,"source":{"id":"https://openalex.org/S4377196265","display_name":"CINECA IRIS Institutial research information system (University of Pisa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I108290504","host_organization_name":"University of Pisa","host_organization_lineage":["https://openalex.org/I108290504"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"pmh:oai:dnet:people______::29ceb9b2965051621f75166039ebfff6","is_oa":false,"landing_page_url":"https://openportal.isti.cnr.it/doc?id=people______::29ceb9b2965051621f75166039ebfff6","pdf_url":null,"source":{"id":"https://openalex.org/S7407055261","display_name":"ISTI Open Portal","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"8th International Conference on Web search and data mining (WSDM 2015), pp. 47\u201356, Shanghai, China, 31/01/2015-06/02/2015","raw_type":"http://purl.org/coar/resource_type/c_5794"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W84899576","https://openalex.org/W1480376833","https://openalex.org/W1524501441","https://openalex.org/W1532325895","https://openalex.org/W1559631118","https://openalex.org/W1963962287","https://openalex.org/W1965172494","https://openalex.org/W1965268014","https://openalex.org/W1965473122","https://openalex.org/W1985136582","https://openalex.org/W1987007212","https://openalex.org/W1991360400","https://openalex.org/W2022292926","https://openalex.org/W2025690557","https://openalex.org/W2032866865","https://openalex.org/W2043909051","https://openalex.org/W2046033161","https://openalex.org/W2057223122","https://openalex.org/W2058150901","https://openalex.org/W2058839679","https://openalex.org/W2065472179","https://openalex.org/W2089455813","https://openalex.org/W2098780214","https://openalex.org/W2135814502","https://openalex.org/W2138662031","https://openalex.org/W2139230733","https://openalex.org/W2140453381","https://openalex.org/W2147028271","https://openalex.org/W2152437528","https://openalex.org/W2154610494","https://openalex.org/W2154615738","https://openalex.org/W2164715417","https://openalex.org/W2263798363","https://openalex.org/W2621280964","https://openalex.org/W2889395214","https://openalex.org/W3102704970","https://openalex.org/W3148153833","https://openalex.org/W4256238177","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W1950940422","https://openalex.org/W4283822356","https://openalex.org/W2129146436","https://openalex.org/W2032507829","https://openalex.org/W2147282173","https://openalex.org/W2151249511"],"abstract_inverted_index":{"Inverted":[0],"indexes":[1,158,165],"are":[2,94,160],"usually":[3],"represented":[4],"by":[5,80],"dividing":[6],"posting":[7],"lists":[8],"into":[9],"constant-sized":[10],"blocks":[11],"and":[12,88,113],"representing":[13],"them":[14],"with":[15,33],"an":[16,49,148],"encoder":[17,121],"for":[18,48,84,122],"sequences":[19],"of":[20,55,73,116,143],"integers.":[21],"Different":[22],"encoders":[23,83],"yield":[24],"a":[25,70,104,110,114,135],"different":[26],"point":[27],"in":[28,65],"the":[29,34,41,53,56,62,66,74,119,128,141,173],"space-time":[30],"trade-off":[31],"curve,":[32],"fastest":[35,57],"being":[36],"several":[37,167],"times":[38],"larger":[39],"than":[40,163],"most":[42],"space-efficient.":[43],"An":[44],"important":[45],"design":[46],"decision":[47],"index":[50,63,124],"is":[51],"thus":[52],"choice":[54,100],"encoding":[58],"method":[59],"such":[60],"that":[61,93,154],"fits":[64],"available":[67],"memory.":[68],"However,":[69],"better":[71],"usage":[72],"space":[75,137,175],"budget":[76],"could":[77],"be":[78],"obtained":[79],"using":[81],"faster":[82,162],"frequently":[85],"accessed":[86],"blocks,":[87],"more":[89],"space-efficient":[90],"ones":[91],"those":[92],"rarely":[95],"accessed.":[96],"To":[97,139],"perform":[98,147],"this":[99,144],"optimally,":[101],"we":[102,146],"introduce":[103],"linear":[105],"time":[106,133],"algorithm":[107,156],"that,":[108],"given":[109,136],"query":[111,131,168],"distribution":[112],"set":[115],"encoders,":[117],"selects":[118],"best":[120],"each":[123],"block":[125],"to":[126],"obtain":[127],"lowest":[129],"expected":[130],"processing":[132,169],"respecting":[134,172],"constraint.":[138],"demonstrate":[140],"effectiveness":[142],"approach":[145],"extensive":[149],"experimental":[150],"analysis,":[151],"which":[152,159],"shows":[153],"our":[155],"produces":[157],"significantly":[161],"single-encoder":[164],"under":[166],"strategies,":[170],"while":[171],"same":[174],"constraints.":[176]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
