{"id":"https://openalex.org/W2579710467","doi":null,"title":"Large-scale Multi-class and Hierarchical Product Categorization for an E-commerce Giant.","display_name":"Large-scale Multi-class and Hierarchical Product Categorization for an E-commerce Giant.","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2579710467","mag":"2579710467"},"language":"en","primary_location":{"id":"mag:2579710467","doi":null,"is_oa":false,"landing_page_url":"https://www.aclweb.org/anthology/C16-1051.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419219","display_name":"International Conference on Computational Linguistics","issn_l":"1525-2477","issn":["1525-2477"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Computational Linguistics","raw_type":null},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"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/A5089229841","display_name":"Ali Cevahir","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I1301041018","display_name":"Rakuten (Japan)","ror":"https://ror.org/0098kke80","country_code":"JP","type":"company","lineage":["https://openalex.org/I1301041018"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ali Cevahir","raw_affiliation_strings":["Rakuten (Japan), Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rakuten (Japan), Tokyo, Japan","institution_ids":["https://openalex.org/I1301041018"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030033498","display_name":"Koji Murakami","orcid":"https://orcid.org/0000-0002-3745-4650","observed_orcids":["https://orcid.org/0000-0002-3745-4650"]},"institutions":[{"id":"https://openalex.org/I75917431","display_name":"Nara Institute of Science and Technology","ror":"https://ror.org/05bhada84","country_code":"JP","type":"education","lineage":["https://openalex.org/I75917431"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Koji Murakami","raw_affiliation_strings":["Nara Institute of Science and Technology, Ikoma, Japan"],"raw_orcid":"https://orcid.org/0000-0002-3745-4650","affiliations":[{"raw_affiliation_string":"Nara Institute of Science and Technology, Ikoma, Japan","institution_ids":["https://openalex.org/I75917431"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6255,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.88671292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"525","last_page":"535"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.7490000128746033,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.7490000128746033,"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/T10028","display_name":"Topic Modeling","score":0.1890999972820282,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.026599999517202377,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/product-classification","display_name":"product classification","score":0.9700000286102295},{"id":"https://openalex.org/keywords/e-commerce","display_name":"e-commerce","score":0.7400000095367432},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"multi-class classification","score":0.7200000286102295},{"id":"https://openalex.org/keywords/hierarchical-taxonomy","display_name":"hierarchical taxonomy","score":0.6340000033378601},{"id":"https://openalex.org/keywords/product-titles","display_name":"product titles","score":0.6790000200271606},{"id":"https://openalex.org/keywords/product-descriptions","display_name":"product descriptions","score":0.9980000257492065},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"deep belief network","score":0.9470000267028809},{"id":"https://openalex.org/keywords/deep-autoencoder","display_name":"deep autoencoder","score":0.9589999914169312},{"id":"https://openalex.org/keywords/gpu-training","display_name":"GPU training","score":0.8180000185966492},{"id":"https://openalex.org/keywords/large-scale-classification","display_name":"large-scale classification","score":0.5270000100135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7774484157562256},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.6724159121513367},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6096176505088806},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5828152298927307},{"id":"https://openalex.org/C58642233","wikidata":"https://www.wikidata.org/wiki/Q8269924","display_name":"Taxonomy (biology)","level":2,"score":0.5802149772644043},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5722951889038086},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5137356519699097},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.507361114025116},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5054192543029785},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4987497329711914},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49451944231987},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.48565971851348877},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46705901622772217},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4370821416378021},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3424643874168396},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3316786587238312},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07802525162696838},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07503530383110046},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0625554621219635},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"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/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/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2579710467","doi":null,"is_oa":false,"landing_page_url":"https://www.aclweb.org/anthology/C16-1051.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419219","display_name":"International Conference on Computational Linguistics","issn_l":"1525-2477","issn":["1525-2477"],"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":["jufo-1"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Computational Linguistics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W137106866","https://openalex.org/W1738364571","https://openalex.org/W1832693441","https://openalex.org/W2012483354","https://openalex.org/W2073830447","https://openalex.org/W2100495367","https://openalex.org/W2120432001","https://openalex.org/W2127099514","https://openalex.org/W2131070108","https://openalex.org/W2136922672","https://openalex.org/W2138806976","https://openalex.org/W2143774383","https://openalex.org/W2149256261","https://openalex.org/W2170240176","https://openalex.org/W2251103205","https://openalex.org/W2265846598","https://openalex.org/W2271752935","https://openalex.org/W2293569829","https://openalex.org/W2510938745","https://openalex.org/W2550446025","https://openalex.org/W2913932916","https://openalex.org/W2963279620"],"related_works":["https://openalex.org/W2919458887","https://openalex.org/W3046054871","https://openalex.org/W2904728018","https://openalex.org/W3154198108","https://openalex.org/W4226143970","https://openalex.org/W2584417445","https://openalex.org/W3091713579","https://openalex.org/W2966837885","https://openalex.org/W2890645506","https://openalex.org/W2553950014"],"abstract_inverted_index":{"In":[0,50],"order":[1,111,123],"to":[2,18,37,59,112,124],"organize":[3],"the":[4,21,25,46,61,99,103,106],"large":[5],"number":[6],"of":[7,20,43,75,105,159,168],"products":[8,47,141,160],"listed":[9],"in":[10,24,110,122,128],"e-commerce":[11],"sites,":[12],"each":[13],"product":[14,67],"is":[15,29],"usually":[16],"assigned":[17],"one":[19],"multi-level":[22],"categories":[23,40,173],"taxonomy":[26,144],"tree.":[27],"It":[28],"a":[30,65,73,94,129,143],"time-consuming":[31],"and":[32,69,84,90],"difficult":[33],"task":[34],"for":[35,45,64,87,98,114,137],"merchants":[36],"select":[38],"proper":[39],"within":[41],"thousands":[42],"options":[44],"they":[48],"sell.":[49],"this":[51],"work,":[52],"we":[53],"propose":[54],"an":[55],"automatic":[56],"classification":[57],"tool":[58],"predict":[60],"matching":[62],"category":[63],"given":[66],"title":[68],"description.":[70],"We":[71,92,132],"used":[72],"combination":[74],"two":[76],"different":[77],"neural":[78,108,126],"models,":[79],"i.e.,":[80],"deep":[81,85,107],"belief":[82],"nets":[83],"autoencoders,":[86],"both":[88],"titles":[89],"descriptions.":[91],"implemented":[93],"selective":[95],"reconstruction":[96],"approach":[97],"input":[100],"layer":[101],"during":[102],"training":[104],"networks,":[109],"scale-out":[113],"large-sized":[115],"sparse":[116],"feature":[117],"vectors.":[118],"GPUs":[119],"are":[120,174],"utilized":[121],"train":[125],"networks":[127],"reasonable":[130],"time.":[131],"have":[133],"trained":[134],"our":[135,163],"models":[136],"around":[138],"150":[139],"million":[140],"with":[142,146,157],"tree":[145],"at":[147],"most":[148],"5":[149],"levels":[150],"that":[151,162],"contains":[152],"28,338":[153],"leaf":[154],"categories.":[155],"Tests":[156],"millions":[158],"show":[161],"first":[164],"predictions":[165],"matches":[166],"81%":[167],"merchants\u2019":[169],"assignments,":[170],"when":[171],"\u201cothers\u201d":[172],"excluded.":[175]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2017-01-26T00:00:00"}