{"id":"https://openalex.org/W4291127509","doi":"https://doi.org/10.1145/3534678.3539158","title":"Graph-based Multilingual Language Model","display_name":"Graph-based Multilingual Language Model","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4291127509","doi":"https://doi.org/10.1145/3534678.3539158"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539158","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534678.3539158","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3534678.3539158","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020049156","display_name":"Nurendra Choudhary","orcid":"https://orcid.org/0000-0002-4471-8968"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nurendra Choudhary","raw_affiliation_strings":["Virginia Tech, Arlington, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Arlington, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081428282","display_name":"Nikhil Rao","orcid":"https://orcid.org/0000-0003-0281-932X"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikhil Rao","raw_affiliation_strings":["Amazon, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021259488","display_name":"Karthik Subbian","orcid":"https://orcid.org/0000-0002-9023-2248"},"institutions":[{"id":"https://openalex.org/I1311688040","display_name":"Amazon (United States)","ror":"https://ror.org/04mv4n011","country_code":"US","type":"company","lineage":["https://openalex.org/I1311688040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karthik Subbian","raw_affiliation_strings":["Amazon, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Amazon, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I1311688040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001022750","display_name":"Chandan K. Reddy","orcid":"https://orcid.org/0000-0003-2839-3662"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chandan K. Reddy","raw_affiliation_strings":["Virginia Tech, Arlington, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Arlington, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5020049156"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":0.3118,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.49935359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2789","last_page":"2799"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9973000288009644,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9973000288009644,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9966999888420105,"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":0.9904000163078308,"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/computer-science","display_name":"Computer science","score":0.8376224040985107},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.6668049097061157},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5313796401023865},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5238223671913147},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4392605721950531},{"id":"https://openalex.org/keywords/query-language","display_name":"Query language","score":0.41731810569763184},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4147856533527374},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.41202133893966675},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.360595703125},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3410632014274597}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8376224040985107},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.6668049097061157},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5313796401023865},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5238223671913147},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4392605721950531},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.41731810569763184},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4147856533527374},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.41202133893966675},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.360595703125},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3410632014274597},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534678.3539158","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534678.3539158","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3534678.3539158","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3534678.3539158","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","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,"raw_source_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6000000238418579,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W2053186076","https://openalex.org/W2102672399","https://openalex.org/W2154851992","https://openalex.org/W2186845332","https://openalex.org/W2387462954","https://openalex.org/W2393319904","https://openalex.org/W2612690371","https://openalex.org/W2737925311","https://openalex.org/W2912500072","https://openalex.org/W2914120296","https://openalex.org/W2962756421","https://openalex.org/W2962946486","https://openalex.org/W2964369530","https://openalex.org/W2998020421","https://openalex.org/W3034844787","https://openalex.org/W3093133157","https://openalex.org/W3104097132","https://openalex.org/W3125508839","https://openalex.org/W4212764525","https://openalex.org/W4212905162"],"related_works":["https://openalex.org/W2382566571","https://openalex.org/W2349321798","https://openalex.org/W2366686860","https://openalex.org/W2350859087","https://openalex.org/W2387118502","https://openalex.org/W4233775131","https://openalex.org/W2020521331","https://openalex.org/W101162712","https://openalex.org/W4256618828","https://openalex.org/W2786691313"],"abstract_inverted_index":{"The":[0,19,119],"large-scale":[1],"nature":[2],"of":[3,10,34,169,205,258],"product":[4,14],"catalog":[5],"and":[6,24,80,101,124,128,150,218,222,266,277,287],"the":[7,78,86,144,156,163,167,203,230,241,246,256,281,292],"changing":[8],"demands":[9],"customer":[11,20,67,79,87,120],"queries":[12,21],"makes":[13],"search":[15,82,94],"a":[16,38,66,97,103,108,132,184,189,214,260],"challenging":[17],"problem.":[18,137],"are":[22],"ambiguous":[23],"implicit.":[25],"They":[26],"may":[27],"be":[28],"looking":[29],"for":[30,65,135,202,279],"an":[31,44,63,284],"exact":[32],"match":[33],"their":[35],"query,":[36],"or":[37,43,71,116],"functional":[39],"equivalent":[40],"(i.e.,":[41,50,264],"substitute),":[42],"accessory":[45],"to":[46,55,84,106,193,228,291],"go":[47],"with":[48,188],"it":[49],"complement).":[51],"It":[52],"is":[53,166,210],"important":[54],"distinguish":[56],"these":[57],"three":[58],"categories":[59],"from":[60],"merely":[61],"classifying":[62],"item":[64],"query":[68,127],"as":[69,96,112,131,148,197,199],"relevant":[70],"not.":[72],"This":[73],"information":[74,134,146,165,201],"can":[75],"help":[76],"direct":[77],"improve":[81],"applications":[83],"understand":[85],"mission.":[88],"In":[89],"this":[90,136],"paper,":[91],"we":[92,273],"formulate":[93],"relevance":[95],"multi-class":[98],"classification":[99,204,248],"problem":[100],"propose":[102,176],"graph-based":[104],"solution":[105],"classify":[107],"given":[109],"query-item":[110],"pair":[111],"exact,":[113],"substitute,":[114],"complement,":[115],"irrelevant":[117],"(ESCI).":[118],"engagement":[121],"(clicks,":[122],"add-to-cart,":[123],"purchases)":[125],"between":[126],"items":[129],"serve":[130],"crucial":[133],"However,":[138],"existing":[139],"approaches":[140],"rely":[141],"purely":[142],"on":[143,155,213,225,245],"textual":[145],"(such":[147],"BERT)":[149],"do":[151],"not":[152],"sufficiently":[153],"focus":[154],"structural":[157,164],"relationships.":[158],"Another":[159],"challenge":[160],"in":[161,172,234,250,268,283],"including":[162],"sparsity":[168],"such":[170],"data":[171,221],"some":[173],"regions.":[174,252],"We":[175,232,253],"Structure-Aware":[177],"multilingual":[178],"LAnguage":[179],"Model":[180],"(SALAM),":[181],"that":[182,237],"utilizes":[183],"language":[185],"model":[186,209,282],"along":[187],"graph":[190,220],"neural":[191],"network,":[192],"extract":[194],"region-specific":[195,226,270],"semantics":[196],"well":[198],"relational":[200],"query-product":[206],"pairs.":[207],"Our":[208],"first":[211],"pre-trained":[212],"large":[215],"region-agnostic":[216],"dataset":[217],"behavioral":[219],"then":[223],"fine-tuned":[224],"versions":[227],"address":[229],"sparsity.":[231],"show":[233],"our":[235],"experiments":[236],"SALAM":[238],"significantly":[239],"outperforms":[240],"current":[242],"matching":[243],"frameworks":[244],"ESCI":[247],"task":[249],"several":[251],"also":[254],"demonstrate":[255],"effectiveness":[257],"using":[259,280],"two-phased":[261],"training":[262],"setup":[263],"pre-training":[265],"fine-tuning)":[267],"capturing":[269],"information.":[271],"Also,":[272],"provide":[274],"various":[275],"challenges":[276],"solutions":[278],"industrial":[285],"setting":[286],"outline":[288],"its":[289],"contribution":[290],"e-commerce":[293],"engine.":[294]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
