{"id":"https://openalex.org/W4411800151","doi":"https://doi.org/10.1109/ccgrid64434.2025.00014","title":"Dynamic Graph Learning for Systems Using Selective State Focused Attention Networks","display_name":"Dynamic Graph Learning for Systems Using Selective State Focused Attention Networks","publication_year":2025,"publication_date":"2025-05-19","ids":{"openalex":"https://openalex.org/W4411800151","doi":"https://doi.org/10.1109/ccgrid64434.2025.00014"},"language":"en","primary_location":{"id":"doi:10.1109/ccgrid64434.2025.00014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccgrid64434.2025.00014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 25th International Symposium on Cluster, Cloud and Internet Computing (CCGrid)","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/A5114534491","display_name":"Shikhar Vashistha","orcid":null},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Shikhar Vashistha","raw_affiliation_strings":["Indian Institute of Technology,Department of Computer Science and Engineering,Roorkee,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Department of Computer Science and Engineering,Roorkee,India","institution_ids":["https://openalex.org/I154851008"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002763824","display_name":"Neetesh Kumar","orcid":"https://orcid.org/0000-0002-0516-1095"},"institutions":[{"id":"https://openalex.org/I154851008","display_name":"Indian Institute of Technology Roorkee","ror":"https://ror.org/00582g326","country_code":"IN","type":"education","lineage":["https://openalex.org/I154851008"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Neetesh Kumar","raw_affiliation_strings":["Indian Institute of Technology,Department of Computer Science and Engineering,Roorkee,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Department of Computer Science and Engineering,Roorkee,India","institution_ids":["https://openalex.org/I154851008"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154851008"],"apc_list":null,"apc_paid":null,"fwci":1.673,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.8234381,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"482","last_page":"492"},"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/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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7552663087844849},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5203551650047302},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4193722903728485},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.41456320881843567},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4107745289802551},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3587193489074707},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.13657215237617493}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7552663087844849},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5203551650047302},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4193722903728485},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.41456320881843567},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4107745289802551},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3587193489074707},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.13657215237617493}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccgrid64434.2025.00014","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccgrid64434.2025.00014","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 25th International Symposium on Cluster, Cloud and Internet Computing (CCGrid)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":89,"referenced_works":["https://openalex.org/W2139823104","https://openalex.org/W2154851992","https://openalex.org/W2407712691","https://openalex.org/W2558460151","https://openalex.org/W2747329762","https://openalex.org/W2804057010","https://openalex.org/W2907492528","https://openalex.org/W2911286998","https://openalex.org/W2916106175","https://openalex.org/W2920929883","https://openalex.org/W2962711740","https://openalex.org/W2962756421","https://openalex.org/W2963312446","https://openalex.org/W2964015378","https://openalex.org/W2964321699","https://openalex.org/W2964915865","https://openalex.org/W2995471443","https://openalex.org/W2997701990","https://openalex.org/W3019011053","https://openalex.org/W3024560045","https://openalex.org/W3099632057","https://openalex.org/W3104097132","https://openalex.org/W3120546985","https://openalex.org/W3121356850","https://openalex.org/W3122137342","https://openalex.org/W3124006607","https://openalex.org/W3126526348","https://openalex.org/W3152893301","https://openalex.org/W3201572672","https://openalex.org/W3209520664","https://openalex.org/W4206482253","https://openalex.org/W4207072731","https://openalex.org/W4239931746","https://openalex.org/W4286795917","https://openalex.org/W4287780403","https://openalex.org/W4289389616","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4308494401","https://openalex.org/W4313598622","https://openalex.org/W4315977496","https://openalex.org/W4321488367","https://openalex.org/W4321609790","https://openalex.org/W4323350086","https://openalex.org/W4367046776","https://openalex.org/W4382119054","https://openalex.org/W4382202909","https://openalex.org/W4386001640","https://openalex.org/W4387196076","https://openalex.org/W4387439537","https://openalex.org/W4390906246","https://openalex.org/W4392157869","https://openalex.org/W4392902681","https://openalex.org/W4393027264","https://openalex.org/W4393140163","https://openalex.org/W4393147196","https://openalex.org/W4393160248","https://openalex.org/W4394866493","https://openalex.org/W4396624100","https://openalex.org/W4396712858","https://openalex.org/W4396759419","https://openalex.org/W4400668005","https://openalex.org/W4404988530","https://openalex.org/W4404993655","https://openalex.org/W4405264897","https://openalex.org/W6639917875","https://openalex.org/W6675747103","https://openalex.org/W6680434193","https://openalex.org/W6699364125","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6754929296","https://openalex.org/W6760001035","https://openalex.org/W6766892243","https://openalex.org/W6771536047","https://openalex.org/W6771932116","https://openalex.org/W6777311388","https://openalex.org/W6777331262","https://openalex.org/W6789174757","https://openalex.org/W6789270503","https://openalex.org/W6839120580","https://openalex.org/W6851435166","https://openalex.org/W6862651651","https://openalex.org/W6863122899","https://openalex.org/W6866011455","https://openalex.org/W6870962703","https://openalex.org/W6875106394","https://openalex.org/W6875136560"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Traditional":[0],"graph":[1,94,128],"neural":[2,52],"networks":[3],"(GNNs)":[4],"lack":[5],"scalability":[6],"and":[7,65,104,111,130,153,156,190,205],"lose":[8],"individual":[9],"node":[10,89,109,115,136],"characteristics":[11],"due":[12],"to":[13,72,85,102],"oversmoothing,":[14],"especially":[15],"in":[16,24,92,107,117],"the":[17,29,74,81,100,124,139,145,158,166,198,209],"case":[18],"of":[19,76,114,126,142,169,173],"deeper":[20],"networks.":[21],"This":[22],"results":[23],"sub-optimal":[25],"feature":[26],"representation,":[27],"affecting":[28],"model's":[30],"performance":[31,167],"on":[32,180,208],"tasks":[33,155],"involving":[34],"dynamically":[35,86,106],"changing":[36,108],"graphs.":[37],"To":[38,164],"address":[39],"this":[40],"issue,":[41],"we":[42],"present":[43],"Graph":[44],"Selective":[45],"state":[46,67],"focused":[47],"Attention":[48],"Networks":[49],"(GSANs)":[50],"based":[51],"network":[53,101,188],"architecture":[54],"for":[55],"graph-structured":[56],"data.":[57],"The":[58,96,120,212],"GSAN":[59,84,149,196],"incorporates":[60],"multi-head":[61],"masked":[62],"self-attention":[63],"(MHMSA)":[64],"sequential":[66],"space":[68],"modeling":[69],"(S3M)":[70],"layers":[71],"overcome":[73],"limitations":[75],"traditional":[77,161],"GNNs.":[78],"In":[79],"GSAN,":[80,170],"MHMSA":[82],"allows":[83],"emphasize":[87],"crucial":[88],"connections,":[90],"particularly":[91],"evolving":[93],"environments.":[95],"S3M":[97,121],"layer":[98,122],"enables":[99],"track":[103],"adjust":[105],"states":[110,137],"improving":[112],"predictions":[113],"behavior":[116,168],"varying":[118],"contexts.":[119],"enhances":[123],"generalization":[125],"unseen":[127],"structures":[129],"provides":[131],"interpretability":[132],"by":[133,201],"analyzing":[134],"how":[135],"affect":[138],"relative":[140],"importance":[141],"links":[143],"within":[144],"graph.":[146],"With":[147],"this,":[148],"effectively":[150],"outperforms":[151],"inductive":[152],"transductive":[154],"overcomes":[157],"issues":[159],"that":[160],"GNNs":[162],"experience.":[163],"analyze":[165],"a":[171],"set":[172],"state-of-theart":[174],"(SOTA)":[175],"comparative":[176],"experiments":[177],"are":[178],"conducted":[179],"graphs":[181],"benchmark":[182],"datasets,":[183],"including":[184],"Cora,":[185],"Citeseer,":[186],"Pubmed":[187],"citation,":[189],"protein-protein-interaction":[191],"datasets.":[192],"As":[193],"an":[194],"outcome,":[195],"improved":[197],"classification":[199],"accuracy":[200],"0.833%,":[202],"0.5%$,":[203],"0.37%,":[204],"1.54":[206],"%":[207],"F1-score,":[210],"respectively.":[211],"code":[213],"is":[214],"publicly":[215],"available":[216],"at":[217],"https://github.com/shikharvashistha/GSAN.":[218]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}