{"id":"https://openalex.org/W4285152239","doi":"https://doi.org/10.18653/v1/2022.findings-acl.225","title":"Extracting Person Names from User Generated Text: Named-Entity Recognition for Combating Human Trafficking","display_name":"Extracting Person Names from User Generated Text: Named-Entity Recognition for Combating Human Trafficking","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4285152239","doi":"https://doi.org/10.18653/v1/2022.findings-acl.225"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.findings-acl.225","pdf_url":"https://aclanthology.org/2022.findings-acl.225.pdf","source":{"id":"https://openalex.org/S4363605144","display_name":"Findings of the Association for Computational Linguistics: ACL 2022","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2022.findings-acl.225.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100355214","display_name":"Yifei Li","orcid":"https://orcid.org/0000-0001-6507-7189"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifei Li","raw_affiliation_strings":["School of Computer Science McGill University Mila -Quebec AI Institute"],"affiliations":[{"raw_affiliation_string":"School of Computer Science McGill University Mila -Quebec AI Institute","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014670663","display_name":"Pratheeksha Nair","orcid":"https://orcid.org/0000-0003-3513-7368"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pratheeksha Nair","raw_affiliation_strings":["School of Computer Science McGill University Mila -Quebec AI Institute"],"affiliations":[{"raw_affiliation_string":"School of Computer Science McGill University Mila -Quebec AI Institute","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057950507","display_name":"Kellin Pelrine","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kellin Pelrine","raw_affiliation_strings":["School of Computer Science McGill University Mila -Quebec AI Institute"],"affiliations":[{"raw_affiliation_string":"School of Computer Science McGill University Mila -Quebec AI Institute","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043159673","display_name":"Reihaneh Rabbany","orcid":"https://orcid.org/0000-0003-2348-0353"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reihaneh Rabbany","raw_affiliation_strings":["School of Computer Science McGill University Mila -Quebec AI Institute"],"affiliations":[{"raw_affiliation_string":"School of Computer Science McGill University Mila -Quebec AI Institute","institution_ids":[]}]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.964,"has_fulltext":true,"fulltext_origin":"pdf","cited_by_count":6,"citation_normalized_percentile":{"value":0.999875,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":85,"max":87},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.9931,"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/T12380","display_name":"Authorship Attribution and Profiling","score":0.9931,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9802,"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/T11644","display_name":"Spam and Phishing Detection","score":0.96,"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/named-entity-recognition","display_name":"Named Entity Recognition","score":0.7467267},{"id":"https://openalex.org/keywords/punctuation","display_name":"Punctuation","score":0.72395545},{"id":"https://openalex.org/keywords/named-entity","display_name":"Named entity","score":0.4741663}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7755608},{"id":"https://openalex.org/C2779135771","wikidata":"https://www.wikidata.org/wiki/Q403574","display_name":"Named-entity recognition","level":3,"score":0.7467267},{"id":"https://openalex.org/C540372491","wikidata":"https://www.wikidata.org/wiki/Q82622","display_name":"Punctuation","level":2,"score":0.72395545},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.64461124},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.57282054},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5170846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5166652},{"id":"https://openalex.org/C26022165","wikidata":"https://www.wikidata.org/wiki/Q8091","display_name":"Grammar","level":2,"score":0.49205083},{"id":"https://openalex.org/C2777889803","wikidata":"https://www.wikidata.org/wiki/Q25047676","display_name":"Named entity","level":2,"score":0.4741663},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42120373},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.20311984},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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":[{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.findings-acl.225","pdf_url":"https://aclanthology.org/2022.findings-acl.225.pdf","source":{"id":"https://openalex.org/S4363605144","display_name":"Findings of the Association for Computational Linguistics: ACL 2022","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.findings-acl.225","pdf_url":"https://aclanthology.org/2022.findings-acl.225.pdf","source":{"id":"https://openalex.org/S4363605144","display_name":"Findings of the Association for Computational Linguistics: ACL 2022","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality","score":0.59}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":42,"referenced_works":["https://openalex.org/W1614298861","https://openalex.org/W1963579188","https://openalex.org/W2015079391","https://openalex.org/W2043089011","https://openalex.org/W2050626994","https://openalex.org/W2096413109","https://openalex.org/W2119130230","https://openalex.org/W2250539671","https://openalex.org/W2296283641","https://openalex.org/W2549416390","https://openalex.org/W2739862888","https://openalex.org/W2755174248","https://openalex.org/W2756894272","https://openalex.org/W2759211898","https://openalex.org/W2760505947","https://openalex.org/W2763129449","https://openalex.org/W2807800730","https://openalex.org/W2857028992","https://openalex.org/W2880875857","https://openalex.org/W2884973659","https://openalex.org/W2896457183","https://openalex.org/W2946602766","https://openalex.org/W2952087486","https://openalex.org/W2953907178","https://openalex.org/W2962739339","https://openalex.org/W2963347649","https://openalex.org/W2963626623","https://openalex.org/W2963997288","https://openalex.org/W2965373594","https://openalex.org/W2987542463","https://openalex.org/W3009654277","https://openalex.org/W3011594683","https://openalex.org/W3035153870","https://openalex.org/W3037109418","https://openalex.org/W3102783139","https://openalex.org/W3104415840","https://openalex.org/W3167077707","https://openalex.org/W3177011560","https://openalex.org/W4288414075","https://openalex.org/W4294170691","https://openalex.org/W4295935503","https://openalex.org/W4301187462"],"related_works":["https://openalex.org/W4386977977","https://openalex.org/W4312792369","https://openalex.org/W3093912612","https://openalex.org/W2983934248","https://openalex.org/W2186562580","https://openalex.org/W2155874911","https://openalex.org/W2032007337","https://openalex.org/W1884363728","https://openalex.org/W1605730749","https://openalex.org/W1516412812"],"abstract_inverted_index":{"Online":[0],"escort":[1,52],"advertisement":[2],"websites":[3],"are":[4],"widely":[5],"used":[6],"for":[7,44,93,140],"advertising":[8,17],"victims":[9],"of":[10,28,37],"human":[11],"trafficking.":[12,29],"Domain":[13],"experts":[14],"agree":[15],"that":[16],"multiple":[18],"people":[19],"in":[20,80,122,135,147],"the":[21,35,57,123,136],"same":[22],"ad":[23],"is":[24,54],"a":[25,106],"strong":[26],"indicator":[27],"Thus,":[30],"extracting":[31,94],"person":[32,95],"names":[33,113],"from":[34],"text":[36,58,124],"these":[38],"ads":[39,53],"can":[40,59],"provide":[41],"valuable":[42],"clues":[43],"further":[45],"analysis.":[46],"However,":[47],"Named-Entity":[48],"Recognition":[49],"(NER)":[50],"on":[51,133],"challenging":[55],"because":[56],"be":[60],"noisy,":[61],"colloquial":[62],"and":[63,68,102,117],"often":[64],"lacking":[65],"proper":[66],"grammar":[67],"punctuation.":[69],"Most":[70],"existing":[71],"state-of-the-art":[72,146],"NER":[73],"models":[74],"fail":[75],"to":[76,110,119,144],"demonstrate":[77],"satisfactory":[78],"performance":[79],"this":[81,84],"task.":[82],"In":[83],"paper,":[85],"we":[86],"propose":[87],"NEAT":[88,129],"(Name":[89],"Extraction":[90],"Against":[91],"Trafficking)":[92],"names.":[96],"It":[97],"effectively":[98],"combines":[99],"classic":[100],"rule-based":[101],"dictionary":[103],"extractors":[104],"with":[105],"contextualized":[107],"language":[108],"model":[109],"capture":[111],"ambiguous":[112],"(e.g":[114],"penny,":[115],"hazel)":[116],"adapts":[118],"adversarial":[120],"changes":[121],"by":[125],"expanding":[126],"its":[127],"dictionary.":[128],"shows":[130],"19%":[131],"improvement":[132],"average":[134],"F1":[137],"classification":[138],"score":[139],"name":[141],"extraction":[142],"compared":[143],"previous":[145],"two":[148],"domain-specific":[149],"datasets.":[150]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4285152239","counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-01-09T02:18:03.028958","created_date":"2022-07-14"}