{"id":"https://openalex.org/W3210877342","doi":"https://doi.org/10.1007/s13278-021-00816-1","title":"Knowledge distillation on neural networks for evolving graphs","display_name":"Knowledge distillation on neural networks for evolving graphs","publication_year":2021,"publication_date":"2021-10-20","ids":{"openalex":"https://openalex.org/W3210877342","doi":"https://doi.org/10.1007/s13278-021-00816-1","mag":"3210877342"},"language":"en","primary_location":{"id":"doi:10.1007/s13278-021-00816-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13278-021-00816-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13278-021-00816-1.pdf","source":{"id":"https://openalex.org/S2764891196","display_name":"Social Network Analysis and Mining","issn_l":"1869-5450","issn":["1869-5450","1869-5469"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Social Network Analysis and Mining","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s13278-021-00816-1.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059198427","display_name":"Stefanos Antaris","orcid":"https://orcid.org/0000-0002-1135-8863"},"institutions":[{"id":"https://openalex.org/I4210091086","display_name":"Hive Streaming (Sweden)","ror":"https://ror.org/00c9zyz36","country_code":"SE","type":"company","lineage":["https://openalex.org/I4210091086"]},{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Stefanos Antaris","raw_affiliation_strings":["HiveStreaming AB, Stockholm, Sweden","KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":"https://orcid.org/0000-0002-1135-8863","affiliations":[{"raw_affiliation_string":"HiveStreaming AB, Stockholm, Sweden","institution_ids":["https://openalex.org/I4210091086"]},{"raw_affiliation_string":"KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034151597","display_name":"Dimitrios Rafailidis","orcid":"https://orcid.org/0000-0002-7366-3716"},"institutions":[{"id":"https://openalex.org/I145722265","display_name":"University of Thessaly","ror":"https://ror.org/04v4g9h31","country_code":"GR","type":"education","lineage":["https://openalex.org/I145722265"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dimitrios Rafailidis","raw_affiliation_strings":["University of Thessaly, V\u00f3los, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Thessaly, V\u00f3los, Greece","institution_ids":["https://openalex.org/I145722265"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041411651","display_name":"\u0160ar\u016bnas Girdzijauskas","orcid":"https://orcid.org/0000-0003-4516-7317"},"institutions":[{"id":"https://openalex.org/I86987016","display_name":"KTH Royal Institute of Technology","ror":"https://ror.org/026vcq606","country_code":"SE","type":"education","lineage":["https://openalex.org/I86987016"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Sarunas Girdzijauskas","raw_affiliation_strings":["KTH Royal Institute of Technology, Stockholm, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KTH Royal Institute of Technology, Stockholm, Sweden","institution_ids":["https://openalex.org/I86987016"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5059198427"],"corresponding_institution_ids":["https://openalex.org/I4210091086","https://openalex.org/I86987016"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.1302,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.59185733,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"11","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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":1.0,"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/T10028","display_name":"Topic Modeling","score":0.989300012588501,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9890999794006348,"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":0.7716981768608093},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6612938642501831},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6306420564651489},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6115525960922241},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5367572903633118},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5323241949081421},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.5165549516677856},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5163763761520386},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49744918942451477},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4270130693912506},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36092865467071533},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.24479928612709045},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.098155677318573}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7716981768608093},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6612938642501831},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6306420564651489},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6115525960922241},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5367572903633118},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5323241949081421},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.5165549516677856},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5163763761520386},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49744918942451477},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4270130693912506},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36092865467071533},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.24479928612709045},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.098155677318573},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","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},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s13278-021-00816-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13278-021-00816-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13278-021-00816-1.pdf","source":{"id":"https://openalex.org/S2764891196","display_name":"Social Network Analysis and Mining","issn_l":"1869-5450","issn":["1869-5450","1869-5469"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Social Network Analysis and Mining","raw_type":"journal-article"},{"id":"pmh:oai:ir.lib.uth.gr:11615/70642","is_oa":false,"landing_page_url":"http://hdl.handle.net/11615/70642","pdf_url":null,"source":{"id":"https://openalex.org/S4306400243","display_name":"University of Thessaly Institutional Repository (University of Thessaly)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I145722265","host_organization_name":"University of Thessaly","host_organization_lineage":["https://openalex.org/I145722265"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Social Network Analysis and Mining","raw_type":"journalArticle"}],"best_oa_location":{"id":"doi:10.1007/s13278-021-00816-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13278-021-00816-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13278-021-00816-1.pdf","source":{"id":"https://openalex.org/S2764891196","display_name":"Social Network Analysis and Mining","issn_l":"1869-5450","issn":["1869-5450","1869-5469"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Social Network Analysis and Mining","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320322509","display_name":"Kungliga Tekniska H\u00f6gskolan","ror":"https://ror.org/026vcq606"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3210877342.pdf","grobid_xml":"https://content.openalex.org/works/W3210877342.grobid-xml"},"referenced_works_count":77,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1971649808","https://openalex.org/W2089554624","https://openalex.org/W2134797427","https://openalex.org/W2153579005","https://openalex.org/W2154851992","https://openalex.org/W2294370754","https://openalex.org/W2519887557","https://openalex.org/W2554952599","https://openalex.org/W2561238782","https://openalex.org/W2594230395","https://openalex.org/W2623187518","https://openalex.org/W2624431344","https://openalex.org/W2700550412","https://openalex.org/W2731516819","https://openalex.org/W2748787960","https://openalex.org/W2755092149","https://openalex.org/W2786915849","https://openalex.org/W2787927827","https://openalex.org/W2788512147","https://openalex.org/W2798918712","https://openalex.org/W2805177834","https://openalex.org/W2806983170","https://openalex.org/W2807021761","https://openalex.org/W2808087697","https://openalex.org/W2808847742","https://openalex.org/W2809279178","https://openalex.org/W2907192581","https://openalex.org/W2911286998","https://openalex.org/W2911778742","https://openalex.org/W2936252403","https://openalex.org/W2945289329","https://openalex.org/W2948162129","https://openalex.org/W2950887295","https://openalex.org/W2954691982","https://openalex.org/W2954901156","https://openalex.org/W2955192706","https://openalex.org/W2962756421","https://openalex.org/W2962949341","https://openalex.org/W2963325573","https://openalex.org/W2963403868","https://openalex.org/W2963456618","https://openalex.org/W2963736842","https://openalex.org/W2963858333","https://openalex.org/W2964118293","https://openalex.org/W2964121744","https://openalex.org/W2965683718","https://openalex.org/W2983247657","https://openalex.org/W2997006708","https://openalex.org/W2998116985","https://openalex.org/W2998313947","https://openalex.org/W3007063652","https://openalex.org/W3012588100","https://openalex.org/W3013104407","https://openalex.org/W3034368386","https://openalex.org/W3034795332","https://openalex.org/W3035321581","https://openalex.org/W3042770487","https://openalex.org/W3089434086","https://openalex.org/W3091441391","https://openalex.org/W3094324529","https://openalex.org/W3094559936","https://openalex.org/W3099375322","https://openalex.org/W3100848837","https://openalex.org/W3101588560","https://openalex.org/W3103254545","https://openalex.org/W3104097132","https://openalex.org/W3108202858","https://openalex.org/W3125024256","https://openalex.org/W3137569190","https://openalex.org/W3138154797","https://openalex.org/W3143870231","https://openalex.org/W3152318512","https://openalex.org/W3161758233","https://openalex.org/W3174102142","https://openalex.org/W3192084854","https://openalex.org/W4210643868"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2055243143","https://openalex.org/W2611989081","https://openalex.org/W3026162553","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W3128807919","https://openalex.org/W3176411177"],"abstract_inverted_index":{"Abstract":[0],"Graph":[1],"representation":[2,34,144],"learning":[3,35,145],"on":[4,12],"dynamic":[5],"graphs":[6],"has":[7],"become":[8],"an":[9,71],"important":[10],"task":[11],"several":[13,169],"real-world":[14],"applications,":[15],"such":[16,54,64],"as":[17],"recommender":[18],"systems,":[19],"email":[20],"spam":[21],"detection,":[22],"and":[23,224],"so":[24],"on.":[25],"To":[26],"efficiently":[27],"capture":[28],"the":[29,50,90,121,130,148,162,183,198,214],"evolution":[30],"of":[31,44,77,127,152,164,180,195],"a":[32,62,85,93,98,137,192,202],"graph,":[33],"approaches":[36,55],"employ":[37],"deep":[38],"neural":[39],"networks,":[40],"with":[41,74,102,124,156,171,201,213],"large":[42,51,94],"amount":[43],"parameters":[45],"to":[46,49,68,70,88,97,118,146],"train.":[47],"Due":[48],"model":[52,96,101,123,167,190],"size,":[53],"have":[56],"high":[57,108],"online":[58],"inference":[59,104,199],"latency.":[60],"As":[61],"consequence,":[63],"models":[65],"are":[66],"challenging":[67],"deploy":[69],"industrial":[72],"setting":[73],"vast":[75],"number":[76],"users/nodes.":[78],"In":[79,133],"this":[80],"study,":[81],"we":[82,135,220],"propose":[83,136],"DynGKD,":[84],"distillation":[86,115,139],"strategy":[87,140],"transfer":[89],"knowledge":[91],"from":[92,129],"teacher":[95,131,215],"small":[99],"student":[100,122],"low":[103],"latency,":[105],"while":[106],"achieving":[107],"prediction":[109,185],"accuracy.":[110],"We":[111],"first":[112],"study":[113],"different":[114,150],"loss":[116],"functions":[117],"separately":[119],"train":[120],"various":[125],"types":[126,151],"information":[128],"model.":[132,216],"addition,":[134],"hybrid":[138],"for":[141],"evolving":[142],"graph":[143],"combine":[147],"teacher\u2019s":[149],"information.":[153],"Our":[154],"experiments":[155],"five":[157],"publicly":[158,226],"available":[159,227],"datasets":[160,223],"demonstrate":[161],"superiority":[163],"our":[165,188,222],"proposed":[166],"against":[168],"baselines,":[170],"average":[172],"relative":[173],"drop":[174],"$$40.60\\%$$":[175],"<mml:math":[176,208],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mrow><mml:mn>40.60</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math>":[177],"in":[178,182],"terms":[179],"RMSE":[181],"link":[184],"task.":[186],"Moreover,":[187],"DynGKD":[189],"achieves":[191],"compression":[193],"ratio":[194],"21:100,":[196],"accelerating":[197],"latency":[200],"speed":[203],"up":[204],"factor":[205],"$$\\times":[206],"30$$":[207],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"><mml:mrow><mml:mo>\u00d7</mml:mo><mml:mn>30</mml:mn></mml:mrow></mml:math>":[209],",":[210],"when":[211],"compared":[212],"For":[217],"reproduction":[218],"purposes,":[219],"make":[221],"implementation":[225],"at":[228],"https://github.com/stefanosantaris/DynGKD":[229],".":[230]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}