{"id":"https://openalex.org/W4290876396","doi":"https://doi.org/10.1145/3534678.3539128","title":"Improving Relevance Modeling via Heterogeneous Behavior Graph Learning in Bing Ads","display_name":"Improving Relevance Modeling via Heterogeneous Behavior Graph Learning in Bing Ads","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4290876396","doi":"https://doi.org/10.1145/3534678.3539128"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539128","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539128","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":null,"license_id":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044362498","display_name":"Bochen Pang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bochen Pang","raw_affiliation_strings":["Microsoft, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037831162","display_name":"Chaozhuo Li","orcid":"https://orcid.org/0000-0002-9867-1712"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chaozhuo Li","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100613983","display_name":"Yuming Liu","orcid":"https://orcid.org/0000-0002-6841-4010"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuming Liu","raw_affiliation_strings":["Microsoft, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087106517","display_name":"Jianxun Lian","orcid":"https://orcid.org/0000-0003-3108-5601"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxun Lian","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103004802","display_name":"Jianan Zhao","orcid":"https://orcid.org/0000-0002-9743-7588"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianan Zhao","raw_affiliation_strings":["University of Notre Dame, Indiana, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Indiana, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037488877","display_name":"Hao Sun","orcid":"https://orcid.org/0000-0001-8456-7925"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Sun","raw_affiliation_strings":["Microsoft, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103206783","display_name":"Weiwei Deng","orcid":"https://orcid.org/0000-0001-6589-2116"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Deng","raw_affiliation_strings":["Microsoft, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044651577","display_name":"Xing Xie","orcid":"https://orcid.org/0000-0002-8608-8482"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Xie","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100360203","display_name":"Qi Zhang","orcid":"https://orcid.org/0000-0001-6076-510X"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zhang","raw_affiliation_strings":["Microsoft, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5044362498"],"corresponding_institution_ids":["https://openalex.org/I4210113369"],"apc_list":null,"apc_paid":null,"fwci":2.0788,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.89134885,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3713","last_page":"3721"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9983000159263611,"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":0.9983000159263611,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9980000257492065,"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"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.996999979019165,"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":0.8071821928024292},{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.6873601078987122},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6725308299064636},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6099789142608643},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5675948858261108},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5243673324584961},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5094192624092102},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3610760569572449},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32231849431991577},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09209063649177551},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.0750112533569336}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8071821928024292},{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.6873601078987122},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6725308299064636},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6099789142608643},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5675948858261108},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5243673324584961},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5094192624092102},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3610760569572449},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32231849431991577},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09209063649177551},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0750112533569336},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534678.3539128","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539128","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":null,"license_id":null,"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":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W189016807","https://openalex.org/W1888005072","https://openalex.org/W1983719983","https://openalex.org/W2113227443","https://openalex.org/W2131876387","https://openalex.org/W2136189984","https://openalex.org/W2139688392","https://openalex.org/W2186845332","https://openalex.org/W2536015822","https://openalex.org/W2539671052","https://openalex.org/W2604202871","https://openalex.org/W2610314927","https://openalex.org/W2808787330","https://openalex.org/W2911286998","https://openalex.org/W2913410650","https://openalex.org/W2913932916","https://openalex.org/W2950193743","https://openalex.org/W2983088090","https://openalex.org/W2989550455","https://openalex.org/W3012871709","https://openalex.org/W3036320503","https://openalex.org/W3098468692","https://openalex.org/W3101681922","https://openalex.org/W3125508839","https://openalex.org/W3156738579","https://openalex.org/W3175971420","https://openalex.org/W3187232099","https://openalex.org/W3212337495","https://openalex.org/W4365799834"],"related_works":["https://openalex.org/W2156910174","https://openalex.org/W1995054232","https://openalex.org/W2011510925","https://openalex.org/W1557920161","https://openalex.org/W1556709767","https://openalex.org/W2468279273","https://openalex.org/W1993023208","https://openalex.org/W4291020658","https://openalex.org/W2593813644","https://openalex.org/W2061476331"],"abstract_inverted_index":{"As":[0],"the":[1,10,13,17,26,32,37,48,65,79,107,148,154,165,172,188],"fundamental":[2],"basis":[3],"of":[4,50,91,110,133,136],"sponsored":[5],"search,":[6],"relevance":[7,21,66,117],"modeling":[8,67,118],"measures":[9],"closeness":[11],"between":[12,157],"input":[14],"queries":[15],"and":[16,75,81,127,160,163,168,183,193],"candidate":[18],"ads.":[19,190],"Conventional":[20],"models":[22],"solely":[23],"rely":[24],"on":[25],"textual":[27,59,166],"data,":[28],"which":[29,61,96],"suffer":[30],"from":[31],"scarce":[33],"semantic":[34],"signals":[35],"within":[36],"short":[38],"queries.":[39],"Recently,":[40],"user":[41,70,92,137],"historical":[42],"click":[43,51],"behaviors":[44,71,93],"are":[45,72],"incorporated":[46],"in":[47,123,187],"format":[49],"graphs":[52],"to":[53,63,78,115,146],"provide":[54,99],"additional":[55],"correlations":[56,156],"beyond":[57],"pure":[58],"semantics,":[60],"contributes":[62],"advancing":[64],"performance.":[68],"However,":[69],"usually":[73],"arbitrary":[74],"unpredictable,":[76],"leading":[77],"noisy":[80],"sparse":[82],"graph":[83,113,131,150,161],"topology.":[84],"In":[85,102],"addition,":[86],"there":[87],"exist":[88],"other":[89],"types":[90,135],"besides":[94],"clicks,":[95],"may":[97],"also":[98],"complementary":[100],"information.":[101],"this":[103],"paper,":[104],"we":[105],"study":[106],"novel":[108,143],"problem":[109],"heterogeneous":[111,129],"behavior":[112,130,149],"learning":[114,124],"facilitate":[116],"task.":[119],"Our":[120,175],"motivation":[121],"lies":[122],"an":[125],"optimal":[126],"task-relevant":[128],"consisting":[132],"multiple":[134],"behaviors.":[138],"We":[139],"further":[140],"propose":[141],"a":[142],"HBGLR":[144],"model":[145],"learn":[147],"structure":[151],"by":[152],"mining":[153],"sophisticated":[155],"node":[158],"semantics":[159,167],"topology,":[162],"encode":[164],"structural":[169],"heterogeneity":[170],"into":[171],"learned":[173],"representations.":[174],"proposal":[176],"is":[177],"evaluated":[178],"over":[179],"real-world":[180],"industry":[181],"datasets,":[182],"has":[184],"been":[185],"mainstreamed":[186],"Bing":[189],"Both":[191],"offline":[192],"online":[194],"experimental":[195],"results":[196],"demonstrate":[197],"its":[198],"superiority.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":14}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}