{"id":"https://openalex.org/W4400529386","doi":"https://doi.org/10.1145/3626772.3661351","title":"A Large-scale Offer Alignment Model for Partitioning Filtering and Matching Product Offers","display_name":"A Large-scale Offer Alignment Model for Partitioning Filtering and Matching Product Offers","publication_year":2024,"publication_date":"2024-07-10","ids":{"openalex":"https://openalex.org/W4400529386","doi":"https://doi.org/10.1145/3626772.3661351"},"language":"en","primary_location":{"id":"doi:10.1145/3626772.3661351","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3626772.3661351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","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/A5070473579","display_name":"Wenyu Huang","orcid":"https://orcid.org/0009-0003-7824-9981"},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Wenyu Huang","raw_affiliation_strings":["The University of Edinburgh, Edinburgh, United Kingdom"],"raw_orcid":"https://orcid.org/0009-0003-7824-9981","affiliations":[{"raw_affiliation_string":"The University of Edinburgh, Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I98677209"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101469138","display_name":"Andr\u00e9 Melo","orcid":"https://orcid.org/0000-0001-6158-7763"},"institutions":[{"id":"https://openalex.org/I4210160618","display_name":"Huawei Technologies (United Kingdom)","ror":"https://ror.org/056gzgs71","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210160618"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andr\u00e9 Melo","raw_affiliation_strings":["Huawei Technologies R&amp;D, Edinburgh, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0001-6158-7763","affiliations":[{"raw_affiliation_string":"Huawei Technologies R&amp;D, Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I4210160618"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066422711","display_name":"Jeff Z. Pan","orcid":"https://orcid.org/0000-0002-9779-2088"},"institutions":[{"id":"https://openalex.org/I4210160618","display_name":"Huawei Technologies (United Kingdom)","ror":"https://ror.org/056gzgs71","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210160618"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jeff Z. Pan","raw_affiliation_strings":["Huawei Technologies R&amp;D, Edinburgh, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-9779-2088","affiliations":[{"raw_affiliation_string":"Huawei Technologies R&amp;D, Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I4210160618"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2880","last_page":"2884"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9937999844551086,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9937999844551086,"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/T11719","display_name":"Data Quality and Management","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10601","display_name":"Handwritten Text Recognition Techniques","score":0.9805999994277954,"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/computer-science","display_name":"Computer science","score":0.6589661836624146},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6274787187576294},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5885940194129944},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5492886304855347},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33346402645111084},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09559524059295654},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06004691123962402}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6589661836624146},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6274787187576294},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5885940194129944},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5492886304855347},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33346402645111084},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09559524059295654},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06004691123962402},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3626772.3661351","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3626772.3661351","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval","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":12,"referenced_works":["https://openalex.org/W2542998387","https://openalex.org/W2794589165","https://openalex.org/W2798649495","https://openalex.org/W2945883855","https://openalex.org/W2952367660","https://openalex.org/W3014705052","https://openalex.org/W3021397474","https://openalex.org/W3123375411","https://openalex.org/W3177179246","https://openalex.org/W4221163653","https://openalex.org/W4306317212","https://openalex.org/W4375869973"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Offer":[0],"alignment":[1,39,54,106,117],"is":[2,41],"a":[3,7],"key":[4,66],"step":[5],"in":[6,43,61],"product":[8,22,27],"knowledge":[9],"graph":[10],"construction":[11],"pipeline.":[12],"It":[13],"aims":[14,49],"to":[15,50,88],"align":[16],"retailer":[17],"offers":[18,91],"of":[19,26,33,68,104],"the":[20,30,37,111],"same":[21],"for":[23,76,99],"better":[24],"coverage":[25],"details.":[28],"With":[29],"rapid":[31],"development":[32],"online":[34],"shopping":[35],"services,":[36],"offer":[38,53,63,74,79,105,116],"task":[40],"applied":[42],"ever":[44],"larger":[45],"datasets.":[46],"This":[47],"work":[48],"build":[51],"an":[52],"system":[55,70,112],"that":[56],"can":[57],"efficiently":[58],"be":[59],"used":[60],"large-scale":[62],"data.":[64],"The":[65],"components":[67],"this":[69],"include:":[71],"1)":[72],"common":[73],"encoders":[75],"encoding":[77],"text":[78],"data":[80],"into":[81,92],"representations;":[82],"2)":[83],"trainable":[84],"LSH":[85],"partitioning":[86],"module":[87],"divide":[89],"similar":[90],"small":[93],"blocks;":[94],"3)":[95],"lightweight":[96],"sophisticated":[97],"late-interactions":[98],"efficient":[100],"filtering":[101],"and":[102,123],"scoring":[103],"candidate":[107],"pairs.":[108],"We":[109],"evaluate":[110],"on":[113],"public":[114],"WDC":[115],"dataset,":[118],"as":[119,121],"well":[120],"DBLP-Scholar":[122],"DBLP-ACM.":[124]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
