{"id":"https://openalex.org/W3012588100","doi":"https://doi.org/10.1145/3366423.3380076","title":"Learning Temporal Interaction Graph Embedding via Coupled Memory Networks","display_name":"Learning Temporal Interaction Graph Embedding via Coupled Memory Networks","publication_year":2020,"publication_date":"2020-04-20","ids":{"openalex":"https://openalex.org/W3012588100","doi":"https://doi.org/10.1145/3366423.3380076","mag":"3012588100"},"language":"en","primary_location":{"id":"doi:10.1145/3366423.3380076","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380076","pdf_url":null,"source":null,"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 Web Conference 2020","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3366423.3380076","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100776748","display_name":"Zhen Zhang","orcid":"https://orcid.org/0000-0001-5769-8786"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhen Zhang","raw_affiliation_strings":["Zhejiang University, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052757755","display_name":"Jiajun Bu","orcid":"https://orcid.org/0000-0002-1097-2044"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiajun Bu","raw_affiliation_strings":["Zhejiang University, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018267399","display_name":"Martin Ester","orcid":"https://orcid.org/0000-0001-7732-2815"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Martin Ester","raw_affiliation_strings":["Simon Fraser University, Canada"],"affiliations":[{"raw_affiliation_string":"Simon Fraser University, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100374719","display_name":"Jianfeng Zhang","orcid":"https://orcid.org/0000-0002-7578-6509"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Zhang","raw_affiliation_strings":["Alibaba Group, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058133483","display_name":"Chengwei Yao","orcid":"https://orcid.org/0000-0002-6035-1502"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengwei Yao","raw_affiliation_strings":["Zhejiang University, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032277491","display_name":"Zhao Li","orcid":"https://orcid.org/0000-0002-5056-0351"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Li","raw_affiliation_strings":["Alibaba Group, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100428572","display_name":"Can Wang","orcid":"https://orcid.org/0000-0002-2890-0057"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Can Wang","raw_affiliation_strings":["Zhejiang University, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100776748"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":4.7721,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.95758016,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"3049","last_page":"3055"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9905999898910522,"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"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.98580002784729,"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":0.7748014330863953},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6984131932258606},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.6097202301025391},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.5748327970504761},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.552897572517395},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49327248334884644},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4787032902240753},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4771817922592163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3687659502029419}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7748014330863953},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6984131932258606},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.6097202301025391},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.5748327970504761},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.552897572517395},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49327248334884644},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4787032902240753},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4771817922592163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3687659502029419},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3366423.3380076","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380076","pdf_url":null,"source":null,"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 Web Conference 2020","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3366423.3380076","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380076","pdf_url":null,"source":null,"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 Web Conference 2020","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1533841329","https://openalex.org/W1793121960","https://openalex.org/W1888005072","https://openalex.org/W1979104937","https://openalex.org/W2062797058","https://openalex.org/W2090891622","https://openalex.org/W2153579005","https://openalex.org/W2154851992","https://openalex.org/W2165515835","https://openalex.org/W2393319904","https://openalex.org/W2525579820","https://openalex.org/W2559094423","https://openalex.org/W2623187518","https://openalex.org/W2624431344","https://openalex.org/W2743104969","https://openalex.org/W2767597557","https://openalex.org/W2783944588","https://openalex.org/W2799012401","https://openalex.org/W2806983170","https://openalex.org/W2808908091","https://openalex.org/W2809001617","https://openalex.org/W2809291355","https://openalex.org/W2950577311","https://openalex.org/W2951777936","https://openalex.org/W2962756421","https://openalex.org/W2963448850","https://openalex.org/W2965683718","https://openalex.org/W2986068433","https://openalex.org/W3029390384","https://openalex.org/W3101588560","https://openalex.org/W3103254545","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2371352078","https://openalex.org/W2953461625","https://openalex.org/W2077383796","https://openalex.org/W2080136900","https://openalex.org/W2372768926","https://openalex.org/W2999799752","https://openalex.org/W2054458431","https://openalex.org/W3013576436","https://openalex.org/W2115167491","https://openalex.org/W2799161558"],"abstract_inverted_index":{"Graph":[0],"embedding":[1],"has":[2],"become":[3],"the":[4,28,127,130,141,150],"research":[5],"focus":[6],"in":[7,27,75,113],"both":[8],"academic":[9],"and":[10,47,64,109,117,124,140],"industrial":[11],"communities":[12],"due":[13],"to":[14,90,107],"its":[15],"powerful":[16],"capabilities.":[17],"The":[18,55],"majority":[19],"of":[20,30,62,97,129],"existing":[21],"work":[22],"overwhelmingly":[23],"learn":[24,91],"node":[25,78,92,111,131],"embeddings":[26,112],"context":[29],"static,":[31],"plain":[32],"or":[33],"attributed,":[34],"homogeneous":[35],"graphs.":[36,54],"However,":[37],"many":[38],"real-world":[39,138],"applications":[40],"frequently":[41],"involve":[42],"bipartite":[43],"graphs":[44],"with":[45,152],"temporal":[46,52,56,98],"attributed":[48],"interaction":[49,53],"edges,":[50],"named":[51,88],"interactions":[57],"usually":[58],"imply":[59],"different":[60,153],"facets":[61],"interest":[63],"might":[65],"even":[66],"evolve":[67],"over":[68],"time,":[69],"thus":[70],"putting":[71],"forward":[72],"huge":[73],"challenges":[74],"learning":[76],"effective":[77],"representations.":[79],"In":[80],"this":[81],"paper,":[82],"we":[83,101],"propose":[84],"a":[85,95],"novel":[86],"framework":[87],"TigeCMN":[89,147],"representations":[93,123],"from":[94],"sequence":[96],"interactions.":[99],"Specifically,":[100],"devise":[102],"two":[103,137],"coupled":[104],"memory":[105],"networks":[106],"store":[108],"update":[110],"external":[114],"matrices":[115],"explicitly":[116],"dynamically,":[118],"which":[119],"forms":[120],"deep":[121],"matrix":[122],"could":[125],"enhance":[126],"expressiveness":[128],"embeddings.":[132],"We":[133],"conduct":[134],"experiments":[135],"on":[136],"datasets":[139],"experimental":[142],"results":[143],"empirically":[144],"demonstrate":[145],"that":[146],"can":[148],"outperform":[149],"state-of-the-arts":[151],"gains.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
