{"id":"https://openalex.org/W3174324482","doi":"https://doi.org/10.1145/3448016.3457315","title":"Identifying Insufficient Data Coverage for Ordinal Continuous-Valued Attributes","display_name":"Identifying Insufficient Data Coverage for Ordinal Continuous-Valued Attributes","publication_year":2021,"publication_date":"2021-06-09","ids":{"openalex":"https://openalex.org/W3174324482","doi":"https://doi.org/10.1145/3448016.3457315","mag":"3174324482"},"language":"en","primary_location":{"id":"doi:10.1145/3448016.3457315","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457315","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457315","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457315","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027319416","display_name":"Abolfazl Asudeh","orcid":"https://orcid.org/0000-0002-5251-6186"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abolfazl Asudeh","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032735930","display_name":"Nima Shahbazi","orcid":"https://orcid.org/0000-0001-7016-3807"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nima Shahbazi","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089174137","display_name":"Zhongjun Jin","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhongjun Jin","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087012731","display_name":"H. V. Jagadish","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"H. V. Jagadish","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5027319416"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":3.919,"has_fulltext":true,"cited_by_count":29,"citation_normalized_percentile":{"value":0.9454993,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"129","last_page":"141"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9984999895095825,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9984999895095825,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9975000023841858,"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":0.9968000054359436,"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/computer-science","display_name":"Computer science","score":0.7348477840423584},{"id":"https://openalex.org/keywords/ordinal-data","display_name":"Ordinal data","score":0.7287052869796753},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.676010251045227},{"id":"https://openalex.org/keywords/ordinal-regression","display_name":"Ordinal regression","score":0.6388189792633057},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5691827535629272},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.5425189137458801},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5204165577888489},{"id":"https://openalex.org/keywords/ordinal-optimization","display_name":"Ordinal optimization","score":0.4665652811527252},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4555943012237549},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4289501905441284},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4014900326728821},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10066431760787964}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7348477840423584},{"id":"https://openalex.org/C85461838","wikidata":"https://www.wikidata.org/wiki/Q7100785","display_name":"Ordinal data","level":2,"score":0.7287052869796753},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.676010251045227},{"id":"https://openalex.org/C110313322","wikidata":"https://www.wikidata.org/wiki/Q7100793","display_name":"Ordinal regression","level":2,"score":0.6388189792633057},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5691827535629272},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.5425189137458801},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5204165577888489},{"id":"https://openalex.org/C81386100","wikidata":"https://www.wikidata.org/wiki/Q7100792","display_name":"Ordinal optimization","level":3,"score":0.4665652811527252},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4555943012237549},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4289501905441284},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4014900326728821},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10066431760787964},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3448016.3457315","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457315","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457315","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3448016.3457315","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3448016.3457315","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3448016.3457315","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 International Conference on Management of Data","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2184854824","display_name":null,"funder_award_id":"1934565","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3150696589","display_name":null,"funder_award_id":"1934565, 1741022","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3710419309","display_name":null,"funder_award_id":"1741022","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5148542160","display_name":null,"funder_award_id":"Research Scholar Award","funder_id":"https://openalex.org/F4320309327","funder_display_name":"Google"},{"id":"https://openalex.org/G7495556737","display_name":null,"funder_award_id":"1741022 and 1934565","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320309327","display_name":"Google","ror":"https://ror.org/00njsd438"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3174324482.pdf","grobid_xml":"https://content.openalex.org/works/W3174324482.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W596522316","https://openalex.org/W1819662813","https://openalex.org/W1967005434","https://openalex.org/W1990643970","https://openalex.org/W1991912219","https://openalex.org/W1993320088","https://openalex.org/W2004809831","https://openalex.org/W2014364956","https://openalex.org/W2039849774","https://openalex.org/W2070164574","https://openalex.org/W2109067131","https://openalex.org/W2109272824","https://openalex.org/W2148239836","https://openalex.org/W2216706082","https://openalex.org/W2282821441","https://openalex.org/W2321124713","https://openalex.org/W2563852449","https://openalex.org/W2695081168","https://openalex.org/W2798497570","https://openalex.org/W2798997222","https://openalex.org/W2807251972","https://openalex.org/W2896331720","https://openalex.org/W2948096245","https://openalex.org/W2948130259","https://openalex.org/W2949752262","https://openalex.org/W2950506967","https://openalex.org/W2951087162","https://openalex.org/W2962762307","https://openalex.org/W2974071289","https://openalex.org/W2987103574","https://openalex.org/W2997315920","https://openalex.org/W3009007872","https://openalex.org/W3031292160","https://openalex.org/W3082499364","https://openalex.org/W3083037709","https://openalex.org/W3085666889","https://openalex.org/W3086107884","https://openalex.org/W3086663505","https://openalex.org/W3102780245","https://openalex.org/W3104279192","https://openalex.org/W3123374861","https://openalex.org/W4220820301","https://openalex.org/W4292081294","https://openalex.org/W4301346705","https://openalex.org/W6638208828","https://openalex.org/W6772730766"],"related_works":["https://openalex.org/W2058716166","https://openalex.org/W2525848170","https://openalex.org/W2023060082","https://openalex.org/W4300104397","https://openalex.org/W4236496007","https://openalex.org/W2050956826","https://openalex.org/W3021328243","https://openalex.org/W2798701209","https://openalex.org/W2237498897","https://openalex.org/W66181126"],"abstract_inverted_index":{"Appropriate":[0],"training":[1,50],"data":[2,38,46,51],"is":[3],"a":[4],"requirement":[5],"for":[6,20,40],"building":[7],"good":[8],"machine-learned":[9],"models.":[10],"In":[11],"this":[12],"paper,":[13],"we":[14],"study":[15],"the":[16,27,30,49],"notion":[17],"of":[18],"coverage":[19],"ordinal":[21],"and":[22],"continuous-valued":[23],"attributes,":[24],"by":[25],"formalizing":[26],"intuition":[28],"that":[29],"learned":[31],"model":[32],"can":[33],"accurately":[34],"predict":[35],"only":[36],"at":[37],"points":[39,47],"which":[41],"there":[42],"are":[43],"\"enough\"":[44],"similar":[45],"in":[48],"set.":[52]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}