{"id":"https://openalex.org/W3107013681","doi":"https://doi.org/10.1145/3423168","title":"PONE","display_name":"PONE","publication_year":2020,"publication_date":"2020-11-13","ids":{"openalex":"https://openalex.org/W3107013681","doi":"https://doi.org/10.1145/3423168","mag":"3107013681"},"language":"en","primary_location":{"id":"doi:10.1145/3423168","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3423168","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-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":null,"display_name":"Tian Lan","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210161752","display_name":"Beijing Haidian Hospital","ror":"https://ror.org/058x5eq06","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210161752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tian Lan","raw_affiliation_strings":["Beijing Institute of Technology, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Haidian, Beijing, China","institution_ids":["https://openalex.org/I125839683","https://openalex.org/I4210161752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017626590","display_name":"Xian-Ling Mao","orcid":"https://orcid.org/0000-0001-6795-2311"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210161752","display_name":"Beijing Haidian Hospital","ror":"https://ror.org/058x5eq06","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210161752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xian-Ling Mao","raw_affiliation_strings":["Beijing Institute of Technology, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Haidian, Beijing, China","institution_ids":["https://openalex.org/I125839683","https://openalex.org/I4210161752"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100323842","display_name":"Wei Wei","orcid":"https://orcid.org/0000-0003-4488-0102"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Wei","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101496429","display_name":"Xiaoyan Gao","orcid":"https://orcid.org/0000-0003-2934-7916"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210161752","display_name":"Beijing Haidian Hospital","ror":"https://ror.org/058x5eq06","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210161752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Gao","raw_affiliation_strings":["Beijing Institute of Technology, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Haidian, Beijing, China","institution_ids":["https://openalex.org/I125839683","https://openalex.org/I4210161752"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087631670","display_name":"Heyan Huang","orcid":"https://orcid.org/0000-0002-0320-7520"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210161752","display_name":"Beijing Haidian Hospital","ror":"https://ror.org/058x5eq06","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210161752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heyan Huang","raw_affiliation_strings":["Beijing Institute of Technology, Haidian, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Haidian, Beijing, China","institution_ids":["https://openalex.org/I125839683","https://openalex.org/I4210161752"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0831,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.93091414,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"39","issue":"1","first_page":"1","last_page":"37"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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/T10028","display_name":"Topic Modeling","score":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9995999932289124,"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/T12031","display_name":"Speech and dialogue systems","score":0.9995999932289124,"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":0.8709233999252319},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.7184269428253174},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6280902028083801},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5811854004859924},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.568290650844574},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5599439144134521},{"id":"https://openalex.org/keywords/open-domain","display_name":"Open domain","score":0.5468024015426636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5184118747711182},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.46647506952285767},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.45241495966911316},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.42552435398101807},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3341695964336395},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07640606164932251}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8709233999252319},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.7184269428253174},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6280902028083801},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5811854004859924},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.568290650844574},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5599439144134521},{"id":"https://openalex.org/C2993776861","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Open domain","level":3,"score":0.5468024015426636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5184118747711182},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.46647506952285767},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.45241495966911316},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.42552435398101807},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3341695964336395},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07640606164932251},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3423168","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3423168","pdf_url":null,"source":{"id":"https://openalex.org/S4394735545","display_name":"ACM Transactions on Information Systems","issn_l":"1046-8188","issn":["1046-8188","1558-2868"],"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":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6044326512","display_name":null,"funder_award_id":"No. 61772076, 61751201 and 61602197","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2101105183","https://openalex.org/W2157331557","https://openalex.org/W2187089797","https://openalex.org/W2408567386","https://openalex.org/W2489487449","https://openalex.org/W2547343769","https://openalex.org/W2584220694","https://openalex.org/W2604799547","https://openalex.org/W2757121784","https://openalex.org/W2781528640","https://openalex.org/W2786273134","https://openalex.org/W2798385473","https://openalex.org/W2807873315","https://openalex.org/W2962786758","https://openalex.org/W2962838727","https://openalex.org/W2962896208","https://openalex.org/W2963216553","https://openalex.org/W2963341956","https://openalex.org/W2963527228","https://openalex.org/W2963625079","https://openalex.org/W2963903950","https://openalex.org/W2964165364","https://openalex.org/W2971190479","https://openalex.org/W2971296908","https://openalex.org/W3015322406","https://openalex.org/W3034715226","https://openalex.org/W4252076394"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W2280377497","https://openalex.org/W3174044702","https://openalex.org/W4238433571","https://openalex.org/W2967848559","https://openalex.org/W4283803360","https://openalex.org/W4317695495","https://openalex.org/W2911655849"],"abstract_inverted_index":{"Open-domain":[0],"generative":[1,38,99],"dialogue":[2,39,100],"systems":[3],"have":[4,173],"attracted":[5],"considerable":[6],"attention":[7],"over":[8],"the":[9,52,92,112,141,166,176],"past":[10],"few":[11],"years.":[12],"Currently,":[13],"how":[14],"to":[15,51,79,123],"automatically":[16],"evaluate":[17],"them":[18],"is":[19,58,65,83],"still":[20],"a":[21,125,134],"big":[22],"challenge.":[23],"As":[24],"far":[25],"as":[26],"we":[27,71,103,132,172],"know,":[28],"there":[29],"are":[30,91],"three":[31],"kinds":[32,76],"of":[33,54,63,77,178],"automatic":[34],"evaluations":[35],"for":[36,97],"open-domain":[37,98],"systems:":[40],"(1)":[41],"Word-overlap-based":[42],"metrics;":[43,46],"(2)":[44],"Embedding-based":[45],"(3)":[47],"Learning-based":[48],"metrics.":[49],"Due":[50],"lack":[53],"systematic":[55],"comparison,":[56],"it":[57],"not":[59],"clear":[60],"which":[61,81,116],"kind":[62,82],"metrics":[64,78,90,96,109],"more":[66],"effective.":[67],"In":[68],"this":[69,130],"article,":[70],"first":[72],"measure":[73],"systematically":[74],"all":[75,107],"check":[80],"best.":[84],"Extensive":[85,159],"experiments":[86,160],"demonstrate":[87,161],"that":[88,105,138,162],"learning-based":[89,108,136,168],"most":[93],"effective":[94],"evaluation":[95,169],"systems.":[101],"Moreover,":[102],"observe":[104],"nearly":[106],"depend":[110],"on":[111],"negative":[113],"sampling":[114],"mechanism,":[115],"obtains":[117],"extremely":[118],"imbalanced":[119],"and":[120,152,182],"low-quality":[121],"samples":[122,151],"train":[124],"score":[126],"model.":[127],"To":[128],"address":[129],"issue,":[131],"propose":[133],"novel":[135],"metric":[137,181],"significantly":[139,164],"improves":[140],"correlation":[142],"with":[143],"human":[144],"judgments":[145],"by":[146],"using":[147],"augmented":[148],"PO":[149],"sitive":[150],"valuable":[153],"NE":[154],"gative":[155],"samples,":[156],"called":[157],"PONE.":[158],"PONE":[163],"outperforms":[165],"state-of-the-art":[167,183],"method.":[170],"Besides,":[171],"publicly":[174],"released":[175],"codes":[177],"our":[179],"proposed":[180],"baselines.":[184],"1":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2020-12-07T00:00:00"}
