{"id":"https://openalex.org/W3123875030","doi":"https://doi.org/10.1109/globecom42002.2020.9322124","title":"Continual Information Cascade Learning","display_name":"Continual Information Cascade Learning","publication_year":2020,"publication_date":"2020-12-01","ids":{"openalex":"https://openalex.org/W3123875030","doi":"https://doi.org/10.1109/globecom42002.2020.9322124","mag":"3123875030"},"language":"en","primary_location":{"id":"doi:10.1109/globecom42002.2020.9322124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom42002.2020.9322124","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","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/A5100403505","display_name":"Fan Zhou","orcid":"https://orcid.org/0000-0002-8038-8150"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Zhou","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101414146","display_name":"Xin Jing","orcid":"https://orcid.org/0000-0002-3425-3968"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Jing","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034170705","display_name":"Xovee Xu","orcid":"https://orcid.org/0000-0001-6415-7558"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xovee Xu","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034789908","display_name":"Ting Zhong","orcid":"https://orcid.org/0000-0002-8163-3146"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Zhong","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086447943","display_name":"Goce Trajcevski","orcid":"https://orcid.org/0000-0002-8839-6278"},"institutions":[{"id":"https://openalex.org/I173911158","display_name":"Iowa State University","ror":"https://ror.org/04rswrd78","country_code":"US","type":"education","lineage":["https://openalex.org/I173911158"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Goce Trajcevski","raw_affiliation_strings":["Iowa State University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Iowa State University, USA","institution_ids":["https://openalex.org/I173911158"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5116212182","display_name":"Jin Wu","orcid":"https://orcid.org/0000-0001-6653-0088"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Wu","raw_affiliation_strings":["University of Electronic Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9994000196456909,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9983999729156494,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.996399998664856,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.8455381393432617},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8294793367385864},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.7525080442428589},{"id":"https://openalex.org/keywords/information-cascade","display_name":"Information cascade","score":0.725450336933136},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7254102826118469},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7217826247215271},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5613287091255188},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5290604829788208},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4787011444568634},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4292733073234558},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4109892249107361},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.22641897201538086}],"concepts":[{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.8455381393432617},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8294793367385864},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.7525080442428589},{"id":"https://openalex.org/C27286358","wikidata":"https://www.wikidata.org/wiki/Q6031027","display_name":"Information cascade","level":2,"score":0.725450336933136},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7254102826118469},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7217826247215271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5613287091255188},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5290604829788208},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4787011444568634},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4292733073234558},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4109892249107361},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.22641897201538086},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom42002.2020.9322124","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom42002.2020.9322124","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2020 - 2020 IEEE Global Communications Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4292040920","display_name":null,"funder_award_id":"CNS 1646107","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5453742210","display_name":null,"funder_award_id":"61602097","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W184915860","https://openalex.org/W1508765177","https://openalex.org/W1682403713","https://openalex.org/W2054476043","https://openalex.org/W2064675550","https://openalex.org/W2125322148","https://openalex.org/W2154851992","https://openalex.org/W2532065816","https://openalex.org/W2551441958","https://openalex.org/W2560647685","https://openalex.org/W2767220239","https://openalex.org/W2786446225","https://openalex.org/W2788388592","https://openalex.org/W2921701073","https://openalex.org/W2926477959","https://openalex.org/W2949377321","https://openalex.org/W2951851909","https://openalex.org/W2952395191","https://openalex.org/W2954973878","https://openalex.org/W2963858333","https://openalex.org/W2964015378","https://openalex.org/W2971779724","https://openalex.org/W2974317861","https://openalex.org/W3047401381","https://openalex.org/W3098511564","https://openalex.org/W3104097132","https://openalex.org/W3104250540","https://openalex.org/W3122471732","https://openalex.org/W3125952634","https://openalex.org/W3134021275","https://openalex.org/W4297733535","https://openalex.org/W4298854966","https://openalex.org/W6726873649","https://openalex.org/W6761283764","https://openalex.org/W6791396901"],"related_works":["https://openalex.org/W2038891404","https://openalex.org/W3104987177","https://openalex.org/W2810784123","https://openalex.org/W3041929574","https://openalex.org/W2990751567","https://openalex.org/W4200012112","https://openalex.org/W2219275368","https://openalex.org/W4385988053","https://openalex.org/W4292369391","https://openalex.org/W2067425759"],"abstract_inverted_index":{"Modeling":[0],"the":[1,11,14,29,42,69,77,124,131,152,161],"information":[2,33,96,111],"diffusion":[3,43,97,112],"process":[4,44],"is":[5,120],"an":[6,46],"essential":[7],"step":[8],"towards":[9],"understanding":[10],"mechanisms":[12],"driving":[13],"success":[15],"of":[16,71,122],"information.":[17],"Existing":[18],"methods":[19],"either":[20],"exploit":[21],"various":[22],"features":[23],"associated":[24],"with":[25,155],"cascades":[26],"to":[27,40,63,68,116],"study":[28],"underlying":[30],"factors":[31],"governing":[32],"propagation,":[34],"or":[35],"leverage":[36],"graph":[37,106],"representation":[38],"techniques":[39],"model":[41,98,162],"in":[45,76],"end-to-end":[47],"manner.":[48],"Current":[49],"solutions":[50],"are":[51],"only":[52,150],"valid":[53],"for":[54,82,109],"a":[55,93],"static":[56],"and":[57,61,84,113,137],"fixed":[58],"observation":[59],"scenario":[60],"fail":[62],"handle":[64],"increasing":[65,117],"observations":[66,128],"due":[67],"challenge":[70],"catastrophic":[72],"forgetting":[73,164],"problems":[74],"inherent":[75],"machine":[78],"learning":[79],"approaches":[80],"used":[81],"modeling":[83,110],"predicting":[85],"cascades.":[86],"To":[87],"remedy":[88],"this":[89],"issue,":[90],"we":[91],"propose":[92],"novel":[94],"dynamic":[95],"CICP":[99,104],"(Continual":[100],"Information":[101],"Cascades":[102],"Prediction).":[103],"employs":[105],"neural":[107],"networks":[108],"continually":[114],"adapts":[115],"observations.":[118],"It":[119],"capable":[121],"capturing":[123],"correlations":[125],"between":[126],"successive":[127],"while":[129],"preserving":[130],"important":[132],"parameters":[133],"regarding":[134],"cascade":[135,143],"evolution":[136],"transition.":[138],"Experiments":[139],"conducted":[140],"on":[141],"real-world":[142],"datasets":[144],"demonstrate":[145],"that":[146],"our":[147],"method":[148],"not":[149],"improves":[151],"prediction":[153],"performance":[154],"accumulated":[156],"data":[157],"but":[158],"also":[159],"prevents":[160],"from":[163],"previously":[165],"trained":[166],"tasks.":[167]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}