{"id":"https://openalex.org/W4229075179","doi":"https://doi.org/10.1145/3477314.3507351","title":"Towards open data discovery","display_name":"Towards open data discovery","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4229075179","doi":"https://doi.org/10.1145/3477314.3507351"},"language":"en","primary_location":{"id":"doi:10.1145/3477314.3507351","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477314.3507351","pdf_url":null,"source":{"id":"https://openalex.org/S4363608665","display_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","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/A5028521068","display_name":"Mar\u00eda Helena Franciscatto","orcid":null},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Maria Helena Franciscatto","raw_affiliation_strings":["Federal University of Paran\u00e1, Curitiba, Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Paran\u00e1, Curitiba, Brazil","institution_ids":["https://openalex.org/I52418104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017981792","display_name":"Marcos Didonet Del Fabro","orcid":"https://orcid.org/0000-0002-8573-6281"},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marcos Didonet Del Fabro","raw_affiliation_strings":["Federal University of Paran\u00e1, Curitiba, Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Paran\u00e1, Curitiba, Brazil","institution_ids":["https://openalex.org/I52418104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019004984","display_name":"C\u00e9lio Trois","orcid":"https://orcid.org/0000-0002-7386-9749"},"institutions":[{"id":"https://openalex.org/I33501960","display_name":"Universidade Federal de Santa Maria","ror":"https://ror.org/01b78mz79","country_code":"BR","type":"education","lineage":["https://openalex.org/I33501960"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Celio Trois","raw_affiliation_strings":["Federal University of Santa Maria, Santa Maria, Brazil"],"affiliations":[{"raw_affiliation_string":"Federal University of Santa Maria, Santa Maria, Brazil","institution_ids":["https://openalex.org/I33501960"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084283545","display_name":"Hegler Tissot","orcid":"https://orcid.org/0000-0003-4635-451X"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hegler Tissot","raw_affiliation_strings":["Drexel University"],"affiliations":[{"raw_affiliation_string":"Drexel University","institution_ids":["https://openalex.org/I72816309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5028521068"],"corresponding_institution_ids":["https://openalex.org/I52418104"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05249063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"713","last_page":"716"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11719","display_name":"Data Quality and Management","score":0.9994999766349792,"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":0.9994999766349792,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9975000023841858,"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":0.9965999722480774,"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/computer-science","display_name":"Computer science","score":0.8218770027160645},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.7269631624221802},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.6619305610656738},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.595741331577301},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5493898987770081},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5139927268028259},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.4247479736804962},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4160105586051941},{"id":"https://openalex.org/keywords/open-data","display_name":"Open data","score":0.41346004605293274},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2874801754951477},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.1736985743045807},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.13642063736915588}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8218770027160645},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.7269631624221802},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.6619305610656738},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.595741331577301},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5493898987770081},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5139927268028259},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.4247479736804962},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4160105586051941},{"id":"https://openalex.org/C2780535194","wikidata":"https://www.wikidata.org/wiki/Q309901","display_name":"Open data","level":2,"score":0.41346004605293274},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2874801754951477},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.1736985743045807},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.13642063736915588},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3477314.3507351","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477314.3507351","pdf_url":null,"source":{"id":"https://openalex.org/S4363608665","display_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1846261984","https://openalex.org/W2171313960","https://openalex.org/W2261521002","https://openalex.org/W2798664493","https://openalex.org/W2971101812","https://openalex.org/W3032215537","https://openalex.org/W3196877232","https://openalex.org/W4299351558"],"related_works":["https://openalex.org/W2389818373","https://openalex.org/W2220831889","https://openalex.org/W2056226831","https://openalex.org/W3013312691","https://openalex.org/W3027421045","https://openalex.org/W4312683641","https://openalex.org/W2576320324","https://openalex.org/W3215994059","https://openalex.org/W3210334372","https://openalex.org/W2980386803"],"abstract_inverted_index":{"Open":[0,50],"Data":[1,51],"discovery":[2],"enables":[3],"the":[4,13,72],"retrieval":[5],"of":[6,89],"data":[7,17],"sources":[8],"most":[9,73],"likely":[10,74],"to":[11,60,76],"contain":[12],"information":[14],"needed,":[15],"facilitating":[16],"access":[18],"and":[19,39,44,70,91],"transparency.":[20],"This":[21],"work":[22],"presents":[23],"a":[24,31,45,94],"comparative":[25],"study":[26],"involving":[27],"three":[28],"different":[29,87],"methods:":[30],"hybrid":[32],"algorithm":[33],"based":[34],"on":[35,57],"Linear":[36],"Discriminant":[37],"Analysis":[38],"Word2Vec,":[40],"Cosine":[41],"similarity":[42],"measure,":[43],"Semantic":[46],"Test":[47],"proposed":[48],"for":[49,99],"search.":[52],"Each":[53],"method":[54],"was":[55],"evaluated":[56],"its":[58],"ability":[59],"discover,":[61],"among":[62],"eight":[63],"open":[64],"datasets,":[65],"using":[66],"only":[67],"their":[68],"metadata":[69],"descriptions,":[71],"one":[75],"meet":[77],"an":[78],"input":[79],"question.":[80],"Three":[81],"evaluation":[82],"rounds":[83],"were":[84],"performed":[85],"with":[86],"sets":[88],"questions":[90],"databases,":[92],"showing":[93],"classification":[95],"accuracy":[96],"above":[97],"81%":[98],"all":[100],"methods.":[101]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
