{"id":"https://openalex.org/W3094540792","doi":"https://doi.org/10.1145/3340531.3411998","title":"Corpus Bootstrapping for Assessment of the Properties of Effectiveness Measures","display_name":"Corpus Bootstrapping for Assessment of the Properties of Effectiveness Measures","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3094540792","doi":"https://doi.org/10.1145/3340531.3411998","mag":"3094540792"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3411998","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411998","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","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/A5041495909","display_name":"Justin Zobel","orcid":"https://orcid.org/0000-0001-6622-032X"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Justin Zobel","raw_affiliation_strings":["University of Melbourne, Parkville, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"University of Melbourne, Parkville, VIC, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031434805","display_name":"Lida Rashidi","orcid":"https://orcid.org/0000-0002-6189-3274"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lida Rashidi","raw_affiliation_strings":["University of Melbourne, Parkville, VIC, Australia"],"affiliations":[{"raw_affiliation_string":"University of Melbourne, Parkville, VIC, Australia","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5041495909"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":1.6015,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.88115624,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1933","last_page":"1952"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9991000294685364,"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/T12072","display_name":"Machine Learning and Algorithms","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"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.984000027179718,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/bootstrapping","display_name":"Bootstrapping (finance)","score":0.9638209342956543},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7683088779449463},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.685276210308075},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5986635088920593},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5424306392669678},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5041185617446899},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48405665159225464},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43763503432273865},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3924964666366577},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.361007422208786},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32765382528305054},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.24612489342689514},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09075003862380981}],"concepts":[{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.9638209342956543},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7683088779449463},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.685276210308075},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5986635088920593},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5424306392669678},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5041185617446899},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48405665159225464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43763503432273865},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3924964666366577},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.361007422208786},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32765382528305054},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.24612489342689514},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09075003862380981},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340531.3411998","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411998","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1968927634","https://openalex.org/W1995945562","https://openalex.org/W2017292914","https://openalex.org/W2022995284","https://openalex.org/W2023772410","https://openalex.org/W2034173707","https://openalex.org/W2037140704","https://openalex.org/W2058896506","https://openalex.org/W2075893676","https://openalex.org/W2077046902","https://openalex.org/W2112688502","https://openalex.org/W2113026607","https://openalex.org/W2120308175","https://openalex.org/W2794432940","https://openalex.org/W2892654592","https://openalex.org/W3132995484","https://openalex.org/W4231484040","https://openalex.org/W7043762925"],"related_works":["https://openalex.org/W1534274833","https://openalex.org/W3117246195","https://openalex.org/W2081850291","https://openalex.org/W156620619","https://openalex.org/W2914363205","https://openalex.org/W1598221548","https://openalex.org/W2150136235","https://openalex.org/W2053591227","https://openalex.org/W2041353081","https://openalex.org/W2581240705"],"abstract_inverted_index":{"Bootstrapping":[0],"is":[1],"an":[2],"established":[3],"tool":[4,168],"for":[5,48,92,169],"examining":[6],"the":[7,26,43,55,66,79,84,87,146],"behaviour":[8,80],"of":[9,28,45,54,57,68,81,86,89,106,128,138,152],"offline":[10],"information":[11],"retrieval":[12],"(IR)":[13],"experiments,":[14],"where":[15],"it":[16],"has":[17],"primarily":[18],"been":[19],"used":[20,40],"to":[21,41,162,172],"assess":[22,42],"statistical":[23],"significance":[24,29],"and":[25,140,150,158,175],"robustness":[27],"tests.":[30],"In":[31],"this":[32],"work":[33],"we":[34],"consider":[35],"how":[36],"bootstrapping":[37,53,73,164],"can":[38,74,95,119,132,155],"be":[39,96,120,133,156],"reliability":[44,139],"effectiveness":[46,82],"measures":[47,99,131,174],"experimental":[49],"IR.":[50],"We":[51,70],"use":[52],"corpus":[56,111,163],"documents":[58],"rather":[59],"than,":[60],"as":[61],"in":[62,123,136,148],"most":[63],"prior":[64],"work,":[65],"set":[67],"queries.":[69],"demonstrate":[71],"that":[72,118,145],"provide":[75],"new":[76],"insights":[77],"into":[78],"measures:":[83],"precision":[85,115],"measurement":[88,149],"a":[90,93,109,114,166],"system":[91,153],"query":[94],"quantified;":[97,121],"some":[98],"are":[100],"more":[101],"consistent":[102],"than":[103],"others;":[104],"rankings":[105],"systems":[107],"on":[108],"test":[110],"likewise":[112],"have":[113],"(or":[116],"uncertainty)":[117],"and,":[122],"experiments":[124],"with":[125],"limited":[126],"volumes":[127],"relevance":[129],"judgements,":[130],"wildly":[134],"different":[135],"terms":[137],"precision.":[141],"Our":[142],"results":[143],"show":[144],"uncertainty":[147],"ranking":[151],"performance":[154],"substantial":[157],"thus":[159],"our":[160],"approach":[161],"provides":[165],"key":[167],"helping":[170],"experimenters":[171],"choose":[173],"understand":[176],"reported":[177],"outcomes.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
