{"id":"https://openalex.org/W4412825983","doi":"https://doi.org/10.1145/3711896.3737069","title":"On the Scalability of Temporal Relative Positional Encoding for Dynamic Link Prediction","display_name":"On the Scalability of Temporal Relative Positional Encoding for Dynamic Link Prediction","publication_year":2025,"publication_date":"2025-08-01","ids":{"openalex":"https://openalex.org/W4412825983","doi":"https://doi.org/10.1145/3711896.3737069"},"language":"en","primary_location":{"id":"doi:10.1145/3711896.3737069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3711896.3737069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","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/A5075529625","display_name":"Ke Cheng","orcid":"https://orcid.org/0000-0002-6063-6129"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ke Cheng","raw_affiliation_strings":["CCSE lab, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"CCSE lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013546812","display_name":"Linzhi Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linzhi Peng","raw_affiliation_strings":["CCSE lab, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"CCSE lab, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036270316","display_name":"Pengyang Wang","orcid":"https://orcid.org/0000-0003-3961-5523"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]},{"id":"https://openalex.org/I6469544","display_name":"City University of Macau","ror":"https://ror.org/04gpd4q15","country_code":"MO","type":"education","lineage":["https://openalex.org/I6469544"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Pengyang Wang","raw_affiliation_strings":["SKL-IOTSC and Department of Computer and Information Science, University of Macau, Macao, China"],"affiliations":[{"raw_affiliation_string":"SKL-IOTSC and Department of Computer and Information Science, University of Macau, Macao, China","institution_ids":["https://openalex.org/I204512498","https://openalex.org/I6469544"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027050251","display_name":"Heng Chang","orcid":"https://orcid.org/0000-0002-4978-8041"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Chang","raw_affiliation_strings":["Huawei Technologies Co., Ltd, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co., Ltd, Beijing, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050337942","display_name":"Junchen Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junchen Ye","raw_affiliation_strings":["School of Transportation Science and Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Transportation Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053487836","display_name":"Bowen Du","orcid":"https://orcid.org/0000-0003-0975-2367"},"institutions":[{"id":"https://openalex.org/I4210126311","display_name":"Beijing Transportation Research Center","ror":"https://ror.org/03pydk223","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210126311"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Du","raw_affiliation_strings":["Zhongguancun Laboratory, Beijing, China and School of Transportation Science and Engineering, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Zhongguancun Laboratory, Beijing, China and School of Transportation Science and Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672","https://openalex.org/I4210126311"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5075529625"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20917449,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"298","last_page":"309"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9962000250816345,"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"}},"topics":[{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9962000250816345,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9884999990463257,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7716158628463745},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6965547204017639},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6918118000030518},{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.6575976610183716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2569405436515808},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.23250243067741394},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.084196537733078}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7716158628463745},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6965547204017639},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6918118000030518},{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.6575976610183716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2569405436515808},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.23250243067741394},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.084196537733078}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3711896.3737069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3711896.3737069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W16334259","https://openalex.org/W398859631","https://openalex.org/W569478347","https://openalex.org/W2908404712","https://openalex.org/W2965683718","https://openalex.org/W2969227524","https://openalex.org/W3035664258","https://openalex.org/W3040558155","https://openalex.org/W3092339997","https://openalex.org/W3114378557","https://openalex.org/W3118906589","https://openalex.org/W4224310030","https://openalex.org/W4310895557","https://openalex.org/W4396722559","https://openalex.org/W4401857350","https://openalex.org/W4401863466","https://openalex.org/W6600168703","https://openalex.org/W6601795639","https://openalex.org/W6605146261"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W1518185400","https://openalex.org/W3200586296","https://openalex.org/W2390279801","https://openalex.org/W4230332972","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W1998033311"],"abstract_inverted_index":{"The":[0],"combination":[1],"of":[2,24],"temporal":[3,45,95,162],"graph":[4,53,58,145],"neural":[5],"networks":[6],"(TGNNs)":[7],"and":[8,44,69,148],"relative":[9,101],"positional":[10,31],"features":[11],"is":[12,113],"effective":[13],"for":[14],"dynamic":[15,57,144],"link":[16,163],"prediction":[17,164],"tasks":[18],"because":[19],"it":[20,93],"improves":[21],"the":[22,30],"modeling":[23],"relationships":[25],"between":[26],"nodes.":[27],"We":[28],"summarize":[29],"feature":[32],"as":[33],"Temporal":[34],"Relative":[35],"Positional":[36],"Encoding":[37],"(TRPE),":[38],"which":[39],"incorporates":[40],"local":[41],"subgraph":[42],"computation":[43,90,106,109],"decay":[46],"effects":[47],"compared":[48,176],"to":[49,73,107,115,177],"RPE":[50],"in":[51,76],"static":[52],"learning.":[54],"However,":[55],"existing":[56,143,153],"learning":[59,146],"methods":[60,147],"with":[61,94,104,135],"TRPE":[62,89,154],"are":[63,139],"limited":[64],"by":[65,91],"high":[66],"computational":[67],"costs":[68],"poor":[70],"scalability":[71,151],"due":[72],"information":[74,103,129],"loss":[75,130],"neighborhood":[77,132],"compression.":[78,133],"To":[79],"address":[80],"this,":[81],"we":[82],"introduce":[83],"a":[84,116],"scalable":[85],"framework":[86,138],"that":[87,167],"enhances":[88],"integrating":[92],"clusters.":[96],"Our":[97,156],"method":[98],"replaces":[99],"high-order":[100],"position":[102],"cluster-based":[105],"reduce":[108],"costs.":[110],"Each":[111],"node":[112],"assigned":[114],"cluster":[117],"based":[118],"on":[119,159],"its":[120],"structural":[121],"role,":[122],"rather":[123],"than":[124,142,152],"just":[125],"randomly":[126],"sketched,":[127],"reducing":[128],"during":[131],"TGNNs":[134],"our":[136,168],"proposed":[137,169],"more":[140],"expressive":[141],"offer":[149],"greater":[150],"models.":[155,179],"experimental":[157],"results":[158],"seven":[160],"standard":[161],"benchmarks":[165],"demonstrate":[166],"model":[170],"achieves":[171],"comparable":[172],"or":[173],"superior":[174],"performance":[175],"state-of-the-art":[178]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}