{"id":"https://openalex.org/W4323520081","doi":"https://doi.org/10.1145/3578741.3578778","title":"Fusing Attribute Type Features for Attribute Value Extraction from Product via Question Answering","display_name":"Fusing Attribute Type Features for Attribute Value Extraction from Product via Question Answering","publication_year":2022,"publication_date":"2022-12-23","ids":{"openalex":"https://openalex.org/W4323520081","doi":"https://doi.org/10.1145/3578741.3578778"},"language":"en","primary_location":{"id":"doi:10.1145/3578741.3578778","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3578741.3578778","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3578741.3578778","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Machine Learning and Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3578741.3578778","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027369574","display_name":"Miaobo Hu","orcid":"https://orcid.org/0000-0002-6417-3280"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Miaobo Hu","raw_affiliation_strings":["University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076518693","display_name":"Jun Xiao","orcid":"https://orcid.org/0000-0002-1799-3948"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Xiao","raw_affiliation_strings":["University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049043187","display_name":"Yunfei Liu","orcid":"https://orcid.org/0000-0002-9362-3447"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210086028","display_name":"Technology and Engineering Center for Space Utilization","ror":"https://ror.org/00cn03n83","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210086028"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfei Liu","raw_affiliation_strings":["Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210086028","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065350469","display_name":"Weihu Guo","orcid":"https://orcid.org/0000-0002-7256-7511"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihu Guo","raw_affiliation_strings":["University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036802437","display_name":"Xipeng Fan","orcid":"https://orcid.org/0000-0002-5506-2896"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xipeng Fan","raw_affiliation_strings":["University of Chinese Academy of Sciences, China"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5027369574"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56025466,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"179","last_page":"184"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9991999864578247,"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":0.9991999864578247,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9986000061035156,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9958999752998352,"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":0.7839703559875488},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.6626898646354675},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5851992964744568},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.5307828187942505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5056471824645996},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5014028549194336},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4991343021392822},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4932040572166443},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4828917980194092},{"id":"https://openalex.org/keywords/attribute-domain","display_name":"Attribute domain","score":0.4652901887893677},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45287805795669556},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4476071894168854},{"id":"https://openalex.org/keywords/type","display_name":"Type (biology)","score":0.44113123416900635},{"id":"https://openalex.org/keywords/variable-and-attribute","display_name":"Variable and attribute","score":0.4248891770839691},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.40676072239875793},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3481467664241791},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23295745253562927},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17411580681800842},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.11290854215621948}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7839703559875488},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.6626898646354675},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5851992964744568},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.5307828187942505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5056471824645996},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5014028549194336},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4991343021392822},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4932040572166443},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4828917980194092},{"id":"https://openalex.org/C75814411","wikidata":"https://www.wikidata.org/wiki/Q4818714","display_name":"Attribute domain","level":3,"score":0.4652901887893677},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45287805795669556},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4476071894168854},{"id":"https://openalex.org/C2777299769","wikidata":"https://www.wikidata.org/wiki/Q3707858","display_name":"Type (biology)","level":2,"score":0.44113123416900635},{"id":"https://openalex.org/C12692103","wikidata":"https://www.wikidata.org/wiki/Q113312","display_name":"Variable and attribute","level":4,"score":0.4248891770839691},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.40676072239875793},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3481467664241791},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23295745253562927},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17411580681800842},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.11290854215621948},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3578741.3578778","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3578741.3578778","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3578741.3578778","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Machine Learning and Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3578741.3578778","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3578741.3578778","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3578741.3578778","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 5th International Conference on Machine Learning and Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4323520081.pdf","grobid_xml":"https://content.openalex.org/works/W4323520081.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W1969221592","https://openalex.org/W1982982698","https://openalex.org/W2020278455","https://openalex.org/W2024105308","https://openalex.org/W2064675550","https://openalex.org/W2147458937","https://openalex.org/W2757732772","https://openalex.org/W2798341154","https://openalex.org/W2896457183","https://openalex.org/W2908018635","https://openalex.org/W2950609341","https://openalex.org/W2950808302","https://openalex.org/W2951865668","https://openalex.org/W2963748441","https://openalex.org/W2998020421","https://openalex.org/W2998636456","https://openalex.org/W3034300118","https://openalex.org/W3115263587","https://openalex.org/W3166701446","https://openalex.org/W3183201745","https://openalex.org/W4226470037"],"related_works":["https://openalex.org/W2362911251","https://openalex.org/W2355009088","https://openalex.org/W2003220380","https://openalex.org/W2361652241","https://openalex.org/W2884866368","https://openalex.org/W2357538651","https://openalex.org/W125606985","https://openalex.org/W1985171608","https://openalex.org/W2810548110","https://openalex.org/W2382857162"],"abstract_inverted_index":{"Extracting":[0],"attribute":[1,12,22,32,51,70,74,82,84,95,103,108,124],"values":[2],"from":[3],"product":[4,31,50],"titles":[5],"is":[6,160],"a":[7,87,132,149],"crucial":[8],"e-commerce":[9],"task.":[10],"Previous":[11],"extraction":[13],"method":[14],"was":[15],"insufficient":[16],"because":[17],"the":[18,37,69,91,102,107,112,119,123,127,136,155],"exist":[19],"dataset":[20,39],"lacked":[21],"type":[23,43,71,85,104],"information.":[24],"To":[25],"overcome":[26],"these":[27],"obstacles":[28],"and":[29,83,89,97,106,115,126],"promote":[30],"research,":[33],"we":[34,55,117],"first":[35],"improve":[36],"AliExpress":[38],"with":[40,86],"appending":[41],"entity":[42],"information":[44,72],"to":[45,66,110,135],"better":[46],"facilitate":[47],"research":[48],"on":[49],"value":[52,75],"extraction.":[53],"Then,":[54],"propose":[56],"an":[57],"Attribute":[58],"Type":[59],"Attention":[60],"via":[61],"Question":[62],"Answering":[63],"(ATAQA)":[64],"approach":[65,143],"fully":[67],"utilize":[68],"for":[73,138],"extraction,":[76],"which":[77],"captures":[78],"semantic":[79],"interaction":[80],"of":[81],"sentence":[88,98],"get":[90,111],"vectors":[92],"containing":[93],"attributes,":[94],"types":[96],"features.":[99],"We":[100],"combine":[101],"vector":[105,109,125],"processed":[113,128],"vector,":[114,129],"then":[116],"use":[118],"self-attention":[120],"layer":[121],"connect":[122],"finally":[130],"export":[131],"sentence-attribute-comprehension":[133],"representation":[134],"CRF":[137],"final":[139],"tagging.":[140],"The":[141],"proposed":[142],"outperforms":[144],"previous":[145],"best":[146],"methods":[147],"by":[148,154],"significant":[150],"margin,":[151],"as":[152],"shown":[153],"experimental":[156],"results.":[157],"Our":[158],"Data":[159],"available":[161],"at":[162],"https://github.com/wandugu/AE-improved.":[163]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}