{"id":"https://openalex.org/W3081199790","doi":"https://doi.org/10.1145/3394486.3403388","title":"Gemini: A Novel and Universal Heterogeneous Graph Information Fusing Framework for Online Recommendations","display_name":"Gemini: A Novel and Universal Heterogeneous Graph Information Fusing Framework for Online Recommendations","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3081199790","doi":"https://doi.org/10.1145/3394486.3403388","mag":"3081199790"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3403388","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; 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/A5101818920","display_name":"Jixing Xu","orcid":"https://orcid.org/0000-0002-6821-6858"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jixing Xu","raw_affiliation_strings":["DiDi BizTech Dept., Beijing, China"],"affiliations":[{"raw_affiliation_string":"DiDi BizTech Dept., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036618593","display_name":"Zhenlong Zhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenlong Zhu","raw_affiliation_strings":["DiDi BizTech Dept., Beijing, China"],"affiliations":[{"raw_affiliation_string":"DiDi BizTech Dept., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045851321","display_name":"Jianxin Zhao","orcid":"https://orcid.org/0000-0002-0198-676X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianxin Zhao","raw_affiliation_strings":["DiDi BizTech Dept., Beijing, China"],"affiliations":[{"raw_affiliation_string":"DiDi BizTech Dept., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060534491","display_name":"Xuanye Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuanye Liu","raw_affiliation_strings":["DiDi BizTech Dept., Beijing, China"],"affiliations":[{"raw_affiliation_string":"DiDi BizTech Dept., Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034699002","display_name":"Minghui Shan","orcid":"https://orcid.org/0009-0001-4824-6566"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Minghui Shan","raw_affiliation_strings":["DiDi BizTech Dept., Beijing, China"],"affiliations":[{"raw_affiliation_string":"DiDi BizTech Dept., Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104493343","display_name":"Jiecheng Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiecheng Guo","raw_affiliation_strings":["DiDi BizTech Dept., Beijing, China"],"affiliations":[{"raw_affiliation_string":"DiDi BizTech Dept., Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101818920"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.605,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.9624768,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3356","last_page":"3365"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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/T11478","display_name":"Caching and Content Delivery","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/generality","display_name":"Generality","score":0.8380122184753418},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7630045413970947},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6329415440559387},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.6008243560791016},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.5185209512710571},{"id":"https://openalex.org/keywords/heterogeneous-network","display_name":"Heterogeneous network","score":0.4652610123157501},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46228671073913574},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.46028605103492737},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32435011863708496},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2504839301109314},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14008432626724243},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.12220928072929382}],"concepts":[{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.8380122184753418},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7630045413970947},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6329415440559387},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.6008243560791016},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.5185209512710571},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.4652610123157501},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46228671073913574},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.46028605103492737},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32435011863708496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2504839301109314},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14008432626724243},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.12220928072929382},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394486.3403388","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394486.3403388","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","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":37,"referenced_works":["https://openalex.org/W1602136775","https://openalex.org/W1662382123","https://openalex.org/W1888005072","https://openalex.org/W2090891622","https://openalex.org/W2136189984","https://openalex.org/W2142535891","https://openalex.org/W2154851992","https://openalex.org/W2475334473","https://openalex.org/W2512971201","https://openalex.org/W2519887557","https://openalex.org/W2534727297","https://openalex.org/W2624431344","https://openalex.org/W2743104969","https://openalex.org/W2767752208","https://openalex.org/W2768532803","https://openalex.org/W2793116255","https://openalex.org/W2798806983","https://openalex.org/W2799012401","https://openalex.org/W2809156873","https://openalex.org/W2809435521","https://openalex.org/W2911840101","https://openalex.org/W2951001079","https://openalex.org/W2951050019","https://openalex.org/W2955659697","https://openalex.org/W2962756421","https://openalex.org/W2963146368","https://openalex.org/W2963512530","https://openalex.org/W2963707260","https://openalex.org/W2970127247","https://openalex.org/W2984074464","https://openalex.org/W3097982973","https://openalex.org/W3098259638","https://openalex.org/W3102205844","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W4230792291","https://openalex.org/W4298289240"],"related_works":["https://openalex.org/W3012371152","https://openalex.org/W4366605471","https://openalex.org/W2159090624","https://openalex.org/W2606945902","https://openalex.org/W2370081772","https://openalex.org/W3036264823","https://openalex.org/W3206528106","https://openalex.org/W2912814903","https://openalex.org/W2123605750","https://openalex.org/W2088740331"],"abstract_inverted_index":{"Recently,":[0],"network":[1,63,73,191],"embedding":[2,95,217],"has":[3],"been":[4],"successfully":[5],"used":[6],"in":[7,43,62,102,210,265],"recommendation":[8,35],"systems.":[9],"Researchers":[10],"have":[11],"made":[12],"efforts":[13],"to":[14,24,41,69,74,97,118,229,251],"utilize":[15],"additional":[16],"auxiliary":[17,29,147],"information":[18,30,64,85,148],"(e.g.,":[19],"social":[20],"relations":[21],"of":[22,93,110,157,177,186,189,267],"users)":[23],"improve":[25],"performance.":[26],"However,":[27],"such":[28],"lacks":[31],"compatibility":[32],"for":[33],"all":[34],"scenarios,":[36],"thus":[37],"it":[38],"is":[39,49,113,208,227],"difficult":[40],"apply":[42],"some":[44,230],"industrial":[45],"scenarios":[46],"where":[47],"generality":[48],"required.":[50],"Moreover,":[51],"the":[52,60,90,99,103,108,123,139,144,155,164,175,205,219,223,233,237,258],"heterogeneous":[53,72,167,202],"nature":[54],"between":[55],"users":[56,178],"and":[57,80,82,130,149,179,197,261],"items":[58,180],"aggravates":[59],"difficulty":[61],"fusion.":[65],"Many":[66],"works":[67],"tried":[68],"transform":[70],"user-item":[71,111,166],"two":[75,170,187],"homogeneous":[76,172,195,212],"graphs":[77,173,184,235],"(i.e.,":[78],"user-user":[79],"item-item),":[81],"then":[83],"fuse":[84],"separately.":[86],"This":[87],"may":[88],"limit":[89],"representation":[91,207],"power":[92],"learned":[94,209],"due":[96],"ignoring":[98],"adjacent":[100,160],"relationship":[101],"original":[104,159,165,238],"graph.":[105],"In":[106],"addition,":[107],"sparsity":[109,225],"interactions":[112],"an":[114,247],"urgent":[115],"problem":[116,226],"need":[117],"be":[119],"solved.":[120],"To":[121],"solve":[122],"above":[124],"problems,":[125],"we":[126,244],"propose":[127,246],"a":[128,151,211],"universal":[129],"effective":[131],"framework":[132],"named":[133],"Gemini,":[134],"which":[135],"only":[136],"relies":[137],"on":[138,146,257],"common":[140],"interaction":[141,224],"logs,":[142],"avoiding":[143],"dependence":[145],"ensuring":[150],"better":[152],"generality.":[153],"For":[154,241],"purpose":[156],"keeping":[158],"relationship,":[161],"Gemini":[162,271],"transforms":[163],"graph":[168],"into":[169],"semi":[171],"from":[174,194,201],"perspective":[176],"respectively.":[181],"The":[182],"transformed":[183,234],"consist":[185],"types":[188],"nodes:":[190],"nodes":[192,196,199],"coming":[193,200],"attribute":[198],"node.":[203],"Then,":[204],"node":[206],"way,":[213],"with":[214],"considering":[215],"edge":[216],"at":[218],"same":[220],"time.":[221],"Simultaneously,":[222],"solved":[228],"extent":[231],"as":[232],"contain":[236],"second-order":[239],"neighbors.":[240],"training":[242,249],"efficiently,":[243],"also":[245],"iterative":[248],"algorithm":[250],"reduce":[252],"computational":[253],"complexity.":[254],"Experimental":[255],"results":[256],"five":[259],"datasets":[260],"online":[262],"A/B":[263],"tests":[264],"recommendations":[266],"DiDiChuXing":[268],"show":[269],"that":[270],"outperforms":[272],"state-of-the-art":[273],"algorithms.":[274]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
