{"id":"https://openalex.org/W2910071410","doi":"https://doi.org/10.1109/icmla.2018.00180","title":"Supervised Transfer Learning for Product Information Question Answering","display_name":"Supervised Transfer Learning for Product Information Question Answering","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2910071410","doi":"https://doi.org/10.1109/icmla.2018.00180","mag":"2910071410"},"language":"en","primary_location":{"id":"doi:10.1109/icmla.2018.00180","doi":"https://doi.org/10.1109/icmla.2018.00180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2018.00180","pdf_url":null,"source":{"id":"https://openalex.org/S4363607906","display_name":"IEEE International Conference on Machine Learning and Applications (ICMLA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1901.02539","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036250098","display_name":"Tuan Lai","orcid":"https://orcid.org/0000-0002-1903-6674","observed_orcids":["https://orcid.org/0000-0002-1903-6674"]},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]},{"id":"https://openalex.org/I2801333002","display_name":"Purdue University System","ror":"https://ror.org/05p8z3f47","country_code":"US","type":"education","lineage":["https://openalex.org/I2801333002"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tuan Manh Lai","raw_affiliation_strings":["Purdue University System, West Lafayette, IN, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University System, West Lafayette, IN, US","institution_ids":["https://openalex.org/I219193219","https://openalex.org/I2801333002"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113663962","display_name":"Trung Bui","orcid":"https://orcid.org/0000-0002-0871-349X","observed_orcids":["https://orcid.org/0000-0002-0871-349X","https://orcid.org/0000-0002-3909-0790"]},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Trung Bui","raw_affiliation_strings":["Adobe Research, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016933602","display_name":"Nedim Lipka","orcid":"https://orcid.org/0000-0002-3779-7784","observed_orcids":["https://orcid.org/0000-0002-3779-7784"]},"institutions":[{"id":"https://openalex.org/I1306409833","display_name":"Adobe Systems (United States)","ror":"https://ror.org/059tvcg64","country_code":"US","type":"company","lineage":["https://openalex.org/I1306409833"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nedim Lipka","raw_affiliation_strings":["Adobe Research, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Adobe Research, USA","institution_ids":["https://openalex.org/I1306409833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100359839","display_name":"Sheng Li","orcid":"https://orcid.org/0000-0003-1205-8632","observed_orcids":["https://orcid.org/0000-0003-1205-8632"]},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sheng Li","raw_affiliation_strings":["University of Georgia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia, USA","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1555,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.89890416,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1109","last_page":"1114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.5214999914169312,"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"}},"topics":[{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.5214999914169312,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.35690000653266907,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.042899999767541885,"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/transfer-learning","display_name":"transfer learning","score":0.906000018119812},{"id":"https://openalex.org/keywords/community-question-answering","display_name":"community question answering","score":0.8679999709129333},{"id":"https://openalex.org/keywords/e-commerce","display_name":"e-commerce","score":0.7139999866485596},{"id":"https://openalex.org/keywords/product-specifications","display_name":"product specifications","score":0.8230000138282776},{"id":"https://openalex.org/keywords/limited-training-data","display_name":"limited training data","score":0.5220000147819519},{"id":"https://openalex.org/keywords/home-depot","display_name":"Home Depot","score":0.9710000157356262}],"concepts":[{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.9027968645095825},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.796270489692688},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.680508017539978},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.62705397605896},{"id":"https://openalex.org/C535291247","wikidata":"https://www.wikidata.org/wiki/Q177567","display_name":"Amazon rainforest","level":2,"score":0.6244816184043884},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6199663877487183},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.595696747303009},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5137571096420288},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.4494936466217041},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43548181653022766},{"id":"https://openalex.org/C3019144022","wikidata":"https://www.wikidata.org/wiki/Q4124998","display_name":"Questions and answers","level":2,"score":0.4198140501976013},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37714114785194397},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3739311993122101},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.3388129472732544},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0757240355014801},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icmla.2018.00180","doi":"https://doi.org/10.1109/icmla.2018.00180","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla.2018.00180","pdf_url":null,"source":{"id":"https://openalex.org/S4363607906","display_name":"IEEE International Conference on Machine Learning and Applications (ICMLA)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1901.02539","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1901.02539","pdf_url":"https://arxiv.org/pdf/1901.02539","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.1901.02539","doi":"https://doi.org/10.48550/arxiv.1901.02539","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1901.02539","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1901.02539","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/1901.02539","pdf_url":"https://arxiv.org/pdf/1901.02539","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1514986335","https://openalex.org/W1902237438","https://openalex.org/W1905882502","https://openalex.org/W2025198378","https://openalex.org/W2062118960","https://openalex.org/W2064675550","https://openalex.org/W2112729630","https://openalex.org/W2118091490","https://openalex.org/W2120735855","https://openalex.org/W2125313055","https://openalex.org/W2125436846","https://openalex.org/W2153579005","https://openalex.org/W2157331557","https://openalex.org/W2165698076","https://openalex.org/W2190067570","https://openalex.org/W2250539671","https://openalex.org/W2251818205","https://openalex.org/W2468484304","https://openalex.org/W2470673105","https://openalex.org/W2481240925","https://openalex.org/W2516995758","https://openalex.org/W2570431255","https://openalex.org/W2587528408","https://openalex.org/W2593833795","https://openalex.org/W2741321799","https://openalex.org/W2760753016","https://openalex.org/W2767857566","https://openalex.org/W2803820154","https://openalex.org/W2872710616","https://openalex.org/W2954153770","https://openalex.org/W2962925243","https://openalex.org/W2963662719","https://openalex.org/W2963748441","https://openalex.org/W3096437212","https://openalex.org/W6630841884"],"related_works":["https://openalex.org/W2118632115","https://openalex.org/W2555213299","https://openalex.org/W2576107865","https://openalex.org/W3215363805","https://openalex.org/W1846393350","https://openalex.org/W3154330131","https://openalex.org/W4307481286","https://openalex.org/W1990306092","https://openalex.org/W4226441484","https://openalex.org/W1973554190"],"abstract_inverted_index":{"Popular":[0],"e-commerce":[1],"websites":[2],"such":[3],"as":[4],"Amazon":[5,94],"offer":[6],"community":[7,35,95],"question":[8,36,96],"answering":[9,37,47,66,97],"systems":[10],"for":[11,46,65,128],"users":[12],"to":[13,50,69],"pose":[14],"product-related":[15],"questions":[16,48,67],"and":[17,53,151],"experienced":[18],"customers":[19],"may":[20],"provide":[21],"answers":[22],"voluntarily.":[23],"In":[24],"this":[25,134,144],"paper,":[26],"we":[27,116,136],"show":[28,152],"that":[29,59],"the":[30,60,73,112,118,121,124,138],"large":[31,82],"volume":[32],"of":[33,62,106,120,123,133],"existing":[34,92],"data":[38,122],"can":[39,77,101],"be":[40,78],"beneficial":[41],"when":[42],"building":[43],"a":[44,63,81,85,147],"system":[45],"related":[49,68],"product":[51],"facts":[52],"specifications.":[54],"Our":[55],"experimental":[56,113],"results":[57],"demonstrate":[58],"performance":[61],"model":[64,141],"products":[70],"listed":[71],"in":[72,103,109,111,143],"Home":[74],"Depot":[75],"website":[76],"improved":[79],"by":[80],"margin":[83],"via":[84],"simple":[86],"transfer":[87],"learning":[88,100],"technique":[89],"from":[90],"an":[91,104,131],"large-scale":[93],"dataset.":[98],"Transfer":[99],"result":[102],"increase":[105],"about":[107],"10%":[108],"accuracy":[110],"setting":[114],"where":[115],"restrict":[117],"size":[119],"target":[125],"task":[126],"used":[127],"training.":[129],"As":[130],"application":[132],"work,":[135],"integrate":[137],"best":[139],"performing":[140],"trained":[142],"work":[145],"into":[146],"mobile-based":[148],"shopping":[149],"assistant":[150],"its":[153],"usefulness.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}