{"id":"https://openalex.org/W3177433205","doi":"https://doi.org/10.1145/3459637.3482015","title":"QuaPy: A Python-Based Framework for Quantification","display_name":"QuaPy: A Python-Based Framework for Quantification","publication_year":2021,"publication_date":"2021-10-26","ids":{"openalex":"https://openalex.org/W3177433205","doi":"https://doi.org/10.1145/3459637.3482015","mag":"3177433205"},"language":"en","primary_location":{"id":"doi:10.1145/3459637.3482015","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2106.11057","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086354805","display_name":"Alejandro Moreo","orcid":"https://orcid.org/0000-0002-0377-1025"},"institutions":[{"id":"https://openalex.org/I4210107558","display_name":"Consorzio Pisa Ricerche","ror":"https://ror.org/01t0n3b84","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210107558"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Alejandro Moreo","raw_affiliation_strings":["Consiglio Nazionale delle Ricerche, Pisa, Italy"],"affiliations":[{"raw_affiliation_string":"Consiglio Nazionale delle Ricerche, Pisa, Italy","institution_ids":["https://openalex.org/I4210107558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082069715","display_name":"Andrea Esuli","orcid":"https://orcid.org/0000-0002-5725-4322"},"institutions":[{"id":"https://openalex.org/I4210107558","display_name":"Consorzio Pisa Ricerche","ror":"https://ror.org/01t0n3b84","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210107558"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Esuli","raw_affiliation_strings":["Consiglio Nazionale delle Ricerche, Pisa, Italy"],"affiliations":[{"raw_affiliation_string":"Consiglio Nazionale delle Ricerche, Pisa, Italy","institution_ids":["https://openalex.org/I4210107558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063975186","display_name":"Fabrizio Sebastiani","orcid":"https://orcid.org/0000-0003-4221-6427"},"institutions":[{"id":"https://openalex.org/I4210107558","display_name":"Consorzio Pisa Ricerche","ror":"https://ror.org/01t0n3b84","country_code":"IT","type":"facility","lineage":["https://openalex.org/I4210107558"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabrizio Sebastiani","raw_affiliation_strings":["Consiglio Nazionale delle Ricerche, Pisa, Italy"],"affiliations":[{"raw_affiliation_string":"Consiglio Nazionale delle Ricerche, Pisa, Italy","institution_ids":["https://openalex.org/I4210107558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5086354805"],"corresponding_institution_ids":["https://openalex.org/I4210107558"],"apc_list":null,"apc_paid":null,"fwci":0.14110358,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53464903,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"4534","last_page":"4543"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13398","display_name":"Data Analysis with R","score":0.9830999970436096,"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/T13398","display_name":"Data Analysis with R","score":0.9830999970436096,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.9805999994277954,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"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/T13650","display_name":"Computational Physics and Python Applications","score":0.9797000288963318,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.9075777530670166},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7437471747398376},{"id":"https://openalex.org/keywords/open-source","display_name":"Open source","score":0.5692508220672607},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5012912750244141},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.4833349883556366},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.48261961340904236},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4672187566757202},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44274333119392395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42972078919410706},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.2387124001979828}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.9075777530670166},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7437471747398376},{"id":"https://openalex.org/C3018397939","wikidata":"https://www.wikidata.org/wiki/Q3644502","display_name":"Open source","level":3,"score":0.5692508220672607},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5012912750244141},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.4833349883556366},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48261961340904236},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4672187566757202},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44274333119392395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42972078919410706},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.2387124001979828}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3459637.3482015","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3459637.3482015","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2106.11057","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.11057","pdf_url":"https://arxiv.org/pdf/2106.11057","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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:3177433205","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2106.11057","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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2106.11057","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2106.11057","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":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2106.11057","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.11057","pdf_url":"https://arxiv.org/pdf/2106.11057","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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1512098439","https://openalex.org/W1919365417","https://openalex.org/W1972047492","https://openalex.org/W2011616828","https://openalex.org/W2067977748","https://openalex.org/W2084933300","https://openalex.org/W2101234009","https://openalex.org/W2110914202","https://openalex.org/W2111084382","https://openalex.org/W2113459411","https://openalex.org/W2141253686","https://openalex.org/W2158243283","https://openalex.org/W2165886501","https://openalex.org/W2171060319","https://openalex.org/W2186678232","https://openalex.org/W2293605466","https://openalex.org/W2460419103","https://openalex.org/W2467434233","https://openalex.org/W2486168876","https://openalex.org/W2757560572","https://openalex.org/W2784045057","https://openalex.org/W2890781652","https://openalex.org/W2939314714","https://openalex.org/W2945276017","https://openalex.org/W2970971581","https://openalex.org/W2974133468","https://openalex.org/W2997591727","https://openalex.org/W3113985549","https://openalex.org/W3120740533","https://openalex.org/W3123899751"],"related_works":["https://openalex.org/W3208623732","https://openalex.org/W3149807132","https://openalex.org/W2770452833","https://openalex.org/W2788915007","https://openalex.org/W3089681385","https://openalex.org/W2541433315","https://openalex.org/W3041214840","https://openalex.org/W3172702655","https://openalex.org/W3057227352","https://openalex.org/W3209463724","https://openalex.org/W2766569870","https://openalex.org/W2079145444","https://openalex.org/W2963029447","https://openalex.org/W2043906184","https://openalex.org/W3124372372","https://openalex.org/W1986636782","https://openalex.org/W3026329562","https://openalex.org/W2758358029","https://openalex.org/W3048400180","https://openalex.org/W2529559689"],"abstract_inverted_index":{"QuaPy":[0,96,131],"is":[1,16,28,88,156],"an":[2],"open-source":[3,157],"framework":[4],"for":[5,94,111,138,145],"performing":[6],"quantification":[7,51,107],"(a.k.a.":[8,36],"supervised":[9,23],"prevalence":[10,37],"estimation),":[11],"written":[12],"in":[13,44,128],"Python.":[14],"Quantification":[15],"the":[17,33,40,129,147,152],"task":[18],"of":[19,39,42,47,99,102,109,115,122,151],"training":[20],"quantifiers":[21],"via":[22,165,171],"learning,":[24],"where":[25],"a":[26,29,45,58,100,162],"quantifier":[27],"predictor":[30],"that":[31,82],"estimates":[32],"relative":[34],"frequencies":[35],"values)":[38],"classes":[41],"interest":[43],"sample":[46],"unlabelled":[48,63],"data.":[49],"While":[50],"can":[52,168],"be":[53,169],"trivially":[54],"performed":[55],"by":[56,90],"applying":[57],"standard":[59],"classifier":[60],"to":[61,75],"each":[62,76],"data":[64,70],"item":[65],"and":[66,85,105,121,141,149,158,167],"counting":[67],"how":[68],"many":[69],"items":[71],"have":[72],"been":[73,80],"assigned":[74],"class,":[77],"it":[78],"has":[79],"shown":[81],"this":[83],"\"classify":[84],"count\"":[86],"method":[87],"outperformed":[89],"methods":[91,104],"specifically":[92],"designed":[93],"quantification.":[95],"provides":[97],"implementations":[98],"number":[101],"baseline":[103],"advanced":[106],"methods,":[108],"routines":[110],"quantification-oriented":[112],"model":[113],"selection,":[114],"several":[116],"broadly":[117],"accepted":[118],"evaluation":[119,124],"measures,":[120],"robust":[123],"protocols":[125],"routinely":[126],"used":[127,137],"field.":[130],"also":[132],"makes":[133],"available":[134,160],"datasets":[135],"commonly":[136],"testing":[139],"quantifiers,":[140],"offers":[142],"visualization":[143],"tools":[144],"facilitating":[146],"analysis":[148],"interpretation":[150],"results.":[153],"The":[154],"software":[155],"publicly":[159],"under":[161],"BSD-3":[163],"licence":[164],"https://github.com/HLT-ISTI/QuaPy,":[166],"installed":[170],"pip":[172],"(https://pypi.org/project/QuaPy/)":[173]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
