{"id":"https://openalex.org/W4399776857","doi":"https://doi.org/10.1145/3665939.3665957","title":"Cocoon: Semantic Table Profiling Using Large Language Models","display_name":"Cocoon: Semantic Table Profiling Using Large Language Models","publication_year":2024,"publication_date":"2024-06-14","ids":{"openalex":"https://openalex.org/W4399776857","doi":"https://doi.org/10.1145/3665939.3665957"},"language":"en","primary_location":{"id":"doi:10.1145/3665939.3665957","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3665939.3665957","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3665939.3665957","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 Workshop on Human-In-the-Loop Data Analytics","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3665939.3665957","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002877429","display_name":"Zezhou Huang","orcid":"https://orcid.org/0009-0002-6613-0337"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zezhou Huang","raw_affiliation_strings":["Columbia University, New York, USA"],"raw_orcid":"https://orcid.org/0009-0002-6613-0337","affiliations":[{"raw_affiliation_string":"Columbia University, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049016095","display_name":"Eugene Wu","orcid":"https://orcid.org/0000-0003-4254-6688"},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eugene Wu","raw_affiliation_strings":["Columbia University, New York, USA"],"raw_orcid":"https://orcid.org/0000-0003-4254-6688","affiliations":[{"raw_affiliation_string":"Columbia University, New York, USA","institution_ids":["https://openalex.org/I78577930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78577930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14280","display_name":"Big Data Technologies and Applications","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9900000095367432,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/profiling","display_name":"Profiling (computer programming)","score":0.7600647211074829},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7528051137924194},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5516213774681091},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.5079765915870667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4322003126144409},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.40722888708114624},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.21289879083633423}],"concepts":[{"id":"https://openalex.org/C187191949","wikidata":"https://www.wikidata.org/wiki/Q1138496","display_name":"Profiling (computer programming)","level":2,"score":0.7600647211074829},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7528051137924194},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5516213774681091},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.5079765915870667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4322003126144409},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.40722888708114624},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.21289879083633423}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3665939.3665957","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3665939.3665957","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3665939.3665957","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 Workshop on Human-In-the-Loop Data Analytics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3665939.3665957","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3665939.3665957","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3665939.3665957","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2024 Workshop on Human-In-the-Loop Data Analytics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2554194520","display_name":"Collaborative Research: CNS CORE: Medium: A Unified Prefetch Framework for Approximation Tolerant Interactive Applications","funder_award_id":"2106197","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3270814614","display_name":null,"funder_award_id":"845638","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3486720790","display_name":"III: Small: Bringing database query optimization to data intensive applications","funder_award_id":"2008295","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5704097577","display_name":"Elements: Open-Source Cyberinfrastructure as a Decision Engine for Socioeconomic Disaster Risk (DESDR)","funder_award_id":"2103794","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7981548635","display_name":"III: Medium: Linear Algebra Operators in Databases to Support Analytic and Machine-Learning Workloads","funder_award_id":"2312991","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/W4399776857.pdf","grobid_xml":"https://content.openalex.org/works/W4399776857.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W2044469685","https://openalex.org/W2083619093","https://openalex.org/W2113411758","https://openalex.org/W2119111481","https://openalex.org/W2119803607","https://openalex.org/W2126848435","https://openalex.org/W2170712852","https://openalex.org/W2751687090","https://openalex.org/W2906330222","https://openalex.org/W2948145720","https://openalex.org/W2949054050","https://openalex.org/W2979452771","https://openalex.org/W3027879771","https://openalex.org/W3118813946","https://openalex.org/W3137001846","https://openalex.org/W4221143046","https://openalex.org/W4385574038","https://openalex.org/W4385714599"],"related_works":["https://openalex.org/W4394360958","https://openalex.org/W2161444195","https://openalex.org/W2589019771","https://openalex.org/W2948670949","https://openalex.org/W4288047943","https://openalex.org/W2985540061","https://openalex.org/W2185012154","https://openalex.org/W4252521128","https://openalex.org/W4287867321","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Data":[0],"profilers":[1,25],"play":[2],"a":[3,68,88],"crucial":[4],"role":[5],"in":[6],"the":[7,58,122],"preprocessing":[8],"phase":[9],"of":[10],"data":[11,69],"analysis":[12],"by":[13,86],"identifying":[14],"quality":[15],"issues":[16],"such":[17,50],"as":[18],"missing,":[19],"extreme,":[20],"or":[21,117],"erroneous":[22],"values.":[23],"Traditionally,":[24],"have":[26],"relied":[27],"solely":[28],"on":[29,57,121],"statistical":[30,77],"methods,":[31],"which":[32],"lead":[33],"to":[34,75],"high":[35],"false":[36,39],"positives":[37],"and":[38,54,95],"negatives.":[40],"For":[41],"example,":[42],"they":[43],"may":[44],"incorrectly":[45],"flag":[46],"missing":[47],"values":[48],"where":[49],"absences":[51],"are":[52,112],"expected":[53],"normal":[55],"based":[56,120],"data's":[59],"semantic":[60],"context.":[61],"To":[62],"address":[63],"these,":[64],"we":[65],"introduce":[66],"Cocoon,":[67],"profiling":[70,78,84],"system":[71],"that":[72,102],"integrates":[73],"LLMs":[74],"imbue":[76],"with":[79],"semantics.":[80],"Cocoon":[81,103],"enhances":[82],"traditional":[83],"methods":[85],"adding":[87],"three-step":[89],"process:":[90],"Semantic":[91,93,96],"Context,":[92],"Profile,":[94],"Review.":[97],"Our":[98],"user":[99],"studies":[100],"show":[101],"is":[104],"highly":[105],"effective":[106],"at":[107],"accurately":[108],"discerning":[109],"whether":[110],"anomalies":[111],"genuine":[113],"errors":[114],"requiring":[115],"correction":[116],"acceptable":[118],"variations":[119],"semantics":[123],"for":[124],"real-world":[125],"datasets.":[126]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}