{"id":"https://openalex.org/W2539023297","doi":"https://doi.org/10.18653/v1/d16-1201","title":"Combining Supervised and Unsupervised Enembles for Knowledge Base Population","display_name":"Combining Supervised and Unsupervised Enembles for Knowledge Base Population","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2539023297","doi":"https://doi.org/10.18653/v1/d16-1201","mag":"2539023297"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d16-1201","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d16-1201","pdf_url":"https://www.aclweb.org/anthology/D16-1201.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D16-1201.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052900932","display_name":"Nazneen Fatema Rajani","orcid":"https://orcid.org/0000-0001-6301-1960"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nazneen Fatema Rajani","raw_affiliation_strings":["Department Of Computer Science The University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department Of Computer Science The University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008715111","display_name":"Raymond J. Mooney","orcid":"https://orcid.org/0000-0002-4504-0490"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raymond Mooney","raw_affiliation_strings":["Department Of Computer Science The University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department Of Computer Science The University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I86519309"],"apc_list":null,"apc_paid":null,"fwci":2.1988,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.90177407,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1943","last_page":"1948"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9605000019073486,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9605000019073486,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.957099974155426,"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/T10320","display_name":"Neural Networks and Applications","score":0.9463000297546387,"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":0.6585676074028015},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.5274805426597595},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45066913962364197},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4487350583076477},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.44723182916641235},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.43082308769226074},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3328724503517151},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12329667806625366},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.056262820959091187}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6585676074028015},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.5274805426597595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45066913962364197},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4487350583076477},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.44723182916641235},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.43082308769226074},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3328724503517151},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12329667806625366},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.056262820959091187},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d16-1201","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d16-1201","pdf_url":"https://www.aclweb.org/anthology/D16-1201.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d16-1201","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d16-1201","pdf_url":"https://www.aclweb.org/anthology/D16-1201.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4713059963","display_name":null,"funder_award_id":"FA8750","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"}],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320338294","display_name":"Air Force Research Laboratory","ror":"https://ror.org/02e2egq70"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2539023297.pdf","grobid_xml":"https://content.openalex.org/works/W2539023297.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W1517678168","https://openalex.org/W1534477342","https://openalex.org/W1781980207","https://openalex.org/W2056451646","https://openalex.org/W2106921868","https://openalex.org/W2110952388","https://openalex.org/W2118585731","https://openalex.org/W2252135867","https://openalex.org/W2294771137","https://openalex.org/W2403515192","https://openalex.org/W2805216012","https://openalex.org/W2805567773","https://openalex.org/W2805756377","https://openalex.org/W2806617565","https://openalex.org/W2916925810","https://openalex.org/W2949524199","https://openalex.org/W2952828185","https://openalex.org/W2962941301"],"related_works":["https://openalex.org/W2385713529","https://openalex.org/W1850639582","https://openalex.org/W4321844043","https://openalex.org/W3196155444","https://openalex.org/W328659180","https://openalex.org/W2599749361","https://openalex.org/W3210156800","https://openalex.org/W3106337462","https://openalex.org/W4297883248","https://openalex.org/W3209574120"],"abstract_inverted_index":{"We":[0,34],"propose":[1],"an":[2],"algorithm":[3],"that":[4,36],"combines":[5],"supervised":[6],"and":[7,27,31,67,73],"unsupervised":[8],"methods":[9],"to":[10,79],"ensemble":[11],"multiple":[12],"systems":[13],"for":[14,42],"two":[15,65],"popular":[16],"Knowledge":[17],"Base":[18],"Population":[19],"(KBP)":[20],"tasks,":[21],"Cold":[22],"Start":[23],"Slot":[24],"Filling":[25],"(CSSF)":[26],"Tri-lingual":[28],"Entity":[29],"Discovery":[30],"Linking":[32],"(TEDL).":[33],"demonstrate":[35],"it":[37],"outperforms":[38],"the":[39,46,71],"best":[40],"system":[41],"both":[43],"tasks":[44],"in":[45],"2015":[47],"competition,":[48],"several":[49],"ensembling":[50],"baselines,":[51],"as":[52,54],"well":[53],"a":[55],"state-of-the-art":[56],"stacking":[57],"approach.":[58],"The":[59],"success":[60],"of":[61,75],"our":[62,76],"technique":[63],"on":[64],"different":[66],"challenging":[68],"problems":[69],"demonstrates":[70],"power":[72],"generality":[74],"combined":[77],"approach":[78],"ensembling.":[80]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
