{"id":"https://openalex.org/W3136715784","doi":"https://doi.org/10.1109/bigdata50022.2020.9378188","title":"Evaluating the Accuracy of Cloud NLP Services Using Ground-Truth Experiments","display_name":"Evaluating the Accuracy of Cloud NLP Services Using Ground-Truth Experiments","publication_year":2020,"publication_date":"2020-12-10","ids":{"openalex":"https://openalex.org/W3136715784","doi":"https://doi.org/10.1109/bigdata50022.2020.9378188","mag":"3136715784"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata50022.2020.9378188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378188","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","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/A5063320659","display_name":"Frank Pallas","orcid":"https://orcid.org/0000-0002-5543-0265"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Frank Pallas","raw_affiliation_strings":["Information Systems Engineering, TU Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Systems Engineering, TU Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049421291","display_name":"Dimitri Staufer","orcid":"https://orcid.org/0009-0000-1671-222X"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dimitri Staufer","raw_affiliation_strings":["Information Systems Engineering, TU Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Systems Engineering, TU Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024739369","display_name":"J\u00f6rn Kuhlenkamp","orcid":null},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jorn Kuhlenkamp","raw_affiliation_strings":["Information Systems Engineering, TU Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Systems Engineering, TU Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4577782"],"apc_list":null,"apc_paid":null,"fwci":0.6772,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.77947238,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"341","last_page":"350"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.996999979019165,"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":0.996999979019165,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9872999787330627,"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/T10260","display_name":"Software Engineering Research","score":0.9679999947547913,"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":0.7990685105323792},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7436733245849609},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.690534234046936},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6142746806144714},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5339272022247314},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5169419646263123},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5041128396987915},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.41233766078948975},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.2905987501144409},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08075833320617676}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7990685105323792},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7436733245849609},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.690534234046936},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6142746806144714},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5339272022247314},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5169419646263123},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5041128396987915},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.41233766078948975},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.2905987501144409},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08075833320617676},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata50022.2020.9378188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata50022.2020.9378188","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1554804307","https://openalex.org/W1602773505","https://openalex.org/W1651603302","https://openalex.org/W2028854421","https://openalex.org/W2108646579","https://openalex.org/W2128065064","https://openalex.org/W2405628490","https://openalex.org/W2471350540","https://openalex.org/W2497265084","https://openalex.org/W2514317811","https://openalex.org/W2612769033","https://openalex.org/W2620898035","https://openalex.org/W2726091402","https://openalex.org/W2742980741","https://openalex.org/W2765507317","https://openalex.org/W2766579252","https://openalex.org/W2888501547","https://openalex.org/W2891077499","https://openalex.org/W2903874970","https://openalex.org/W3005810250","https://openalex.org/W3014216516","https://openalex.org/W3100025589","https://openalex.org/W4289493521","https://openalex.org/W6755050132","https://openalex.org/W7056464119"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W4389340727","https://openalex.org/W3150465815","https://openalex.org/W1997222214","https://openalex.org/W2802581102","https://openalex.org/W4205786897","https://openalex.org/W2070395303"],"abstract_inverted_index":{"Cloud":[0],"services":[1,52,72,98,104,176],"for":[2,90,105,142,154,169,177],"natural":[3,41],"language":[4,42],"processing":[5],"(NLP)":[6],"increasingly":[7],"establish":[8],"as":[9,73,75,123,125,166],"viable":[10],"alternatives":[11],"to":[12,36,78,102,151],"self-maintained":[13],"and":[14,25,32,99,115],"self-trained":[15],"NLP":[16,51,97,108,155,175],"pipelines.":[17],"In":[18],"particular,":[19],"they":[20],"feature":[21],"low":[22],"access":[23],"barriers":[24],"management":[26],"overhead,":[27],"a":[28,88,143,167],"pay-as-you-go":[29],"pricing":[30],"model,":[31],"elastic":[33],"scalability":[34],"allowing":[35],"process":[37],"large":[38],"amounts":[39],"of":[40,131,148,173],"data":[43,133],"ad":[44],"hoc.":[45],"Any":[46],"deliberation":[47],"about":[48,66,76],"employing":[49],"cloud":[50,96,103,174],"in":[53,156],"practice":[54],"does,":[55],"however,":[56],"face":[57],"the":[58,67,92,129,135,149,159],"challenge":[59],"that":[60],"so":[61],"far,":[62],"little":[63],"is":[64],"known":[65],"accuracy":[68,93],"provided":[69,94],"by":[70,95,111,182],"such":[71],"well":[74,124],"how":[77],"conduct":[79],"respective":[80],"quality":[81],"assessments.In":[82],"this":[83],"paper,":[84],"we":[85],"therefore":[86,140],"present":[87],"method":[89],"evaluating":[91],"apply":[100],"it":[101],"three":[106],"prominent":[107],"tasks":[109,179],"offered":[110,181],"Amazon,":[112],"Google,":[113],"Microsoft,":[114],"IBM.":[116],"Our":[117,138],"results":[118],"show":[119],"significantly":[120],"different":[121,126],"accuracies":[122],"dependencies":[127],"on":[128],"specifics":[130],"input":[132],"among":[134],"covered":[136],"providers.":[137,184],"insights":[139],"allow":[141],"more":[144],"evidence-based":[145],"quality-driven":[146],"choice":[147],"provider":[150],"be":[152],"used":[153],"practice.":[157],"Furthermore,":[158],"general":[160],"approach":[161],"employed":[162],"may":[163],"also":[164],"serve":[165],"blueprint":[168],"additional":[170],"future":[171],"evaluations":[172],"other":[178,183],"or":[180]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
