{"id":"https://openalex.org/W4407953142","doi":"https://doi.org/10.1145/3701551.3703492","title":"Hyperdimensional Representation Learning for Node Classification and Link Prediction","display_name":"Hyperdimensional Representation Learning for Node Classification and Link Prediction","publication_year":2025,"publication_date":"2025-02-26","ids":{"openalex":"https://openalex.org/W4407953142","doi":"https://doi.org/10.1145/3701551.3703492"},"language":"en","primary_location":{"id":"doi:10.1145/3701551.3703492","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701551.3703492","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701551.3703492?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3701551.3703492?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5094027934","display_name":"Abhishek Dalvi","orcid":null},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Abhishek Dalvi","raw_affiliation_strings":["The Pennsylvania State University, University Park, Pennsylvania, USA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, Pennsylvania, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004737962","display_name":"Vasant Honavar","orcid":"https://orcid.org/0000-0001-5399-3489"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vasant Honavar","raw_affiliation_strings":["The Pennsylvania State University, University Park, Pennsylvania, USA"],"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, University Park, Pennsylvania, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5094027934"],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":9.3096,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.97219038,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"88","last_page":"97"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9965999722480774,"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":0.9965999722480774,"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":0.9872999787330627,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9689000248908997,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/link","display_name":"Link (geometry)","score":0.721471905708313},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6715837121009827},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.645923376083374},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5787811279296875},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4958866536617279},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.434480756521225},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.17745301127433777},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0876399576663971}],"concepts":[{"id":"https://openalex.org/C2778753846","wikidata":"https://www.wikidata.org/wiki/Q6554239","display_name":"Link (geometry)","level":2,"score":0.721471905708313},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6715837121009827},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.645923376083374},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5787811279296875},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4958866536617279},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.434480756521225},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.17745301127433777},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0876399576663971},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","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:10.1145/3701551.3703492","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701551.3703492","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701551.3703492?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3701551.3703492","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3701551.3703492","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3701551.3703492?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4817966223","display_name":null,"funder_award_id":"2226025","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4906924687","display_name":null,"funder_award_id":"TR002014","funder_id":"https://openalex.org/F4320337472","funder_display_name":"National Center for Advancing Translational Sciences"},{"id":"https://openalex.org/G5479771300","display_name":null,"funder_award_id":"UL1 TR002014","funder_id":"https://openalex.org/F4320337472","funder_display_name":"National Center for Advancing Translational Sciences"},{"id":"https://openalex.org/G5485640565","display_name":null,"funder_award_id":"2226025","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"},{"id":"https://openalex.org/G5558081089","display_name":null,"funder_award_id":"UL1 TR002","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G6190180749","display_name":null,"funder_award_id":"UL1 TR002014","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7544350372","display_name":null,"funder_award_id":"TR002014","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"},{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337472","display_name":"National Center for Advancing Translational Sciences","ror":"https://ror.org/04pw6fb54"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4407953142.pdf","grobid_xml":"https://content.openalex.org/works/W4407953142.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W1731012987","https://openalex.org/W2012833704","https://openalex.org/W2066636486","https://openalex.org/W2127827747","https://openalex.org/W2147717514","https://openalex.org/W2154851992","https://openalex.org/W2162630660","https://openalex.org/W2166681504","https://openalex.org/W2168190036","https://openalex.org/W2168627253","https://openalex.org/W2583803680","https://openalex.org/W2907492528","https://openalex.org/W2963224980","https://openalex.org/W2963512530","https://openalex.org/W2974428947","https://openalex.org/W3019494121","https://openalex.org/W3019791076","https://openalex.org/W3028571922","https://openalex.org/W3033330790","https://openalex.org/W3037032032","https://openalex.org/W3104097132","https://openalex.org/W3105115497","https://openalex.org/W3108202858","https://openalex.org/W3112858938","https://openalex.org/W3162323195","https://openalex.org/W3204836041","https://openalex.org/W3205849499","https://openalex.org/W3210619801","https://openalex.org/W3214202924","https://openalex.org/W4210566186","https://openalex.org/W4285086368","https://openalex.org/W4293216350","https://openalex.org/W4312190978","https://openalex.org/W4312210066","https://openalex.org/W4312991481","https://openalex.org/W4322153971","https://openalex.org/W4387494819","https://openalex.org/W4388037272","https://openalex.org/W4389166776"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"We":[0,103],"introduce":[1],"Hyperdimensional":[2],"Graph":[3,43],"Learner":[4],"(HDGL),":[5],"a":[6,22,40,96],"novel":[7],"method":[8],"for":[9,30],"node":[10,19,37,66,69,75,118],"classification":[11,76,119],"and":[12,47,55,77,91,139,151],"link":[13,78,142],"prediction":[14,79,143],"in":[15,39],"graphs.":[16],"HDGL":[17,121,145],"maps":[18],"features":[20],"into":[21],"very":[23],"high-dimensional":[24],"space":[25,29],"(hyperdimensional":[26],"or":[27],"HD":[28,50],"short)":[31],"using":[32,108],"the":[33,61,100,117,130,141,147],"injectivity":[34],"property":[35],"of":[36,42,64,106,129,149,158],"representations":[38,70],"family":[41],"Neural":[44],"Networks":[45],"(GNNs)":[46],"then":[48],"uses":[49],"operators":[51],"such":[52],"as":[53],"bundling":[54],"binding":[56],"to":[57],"aggregate":[58],"information":[59],"from":[60],"local":[62],"neighborhood":[63],"each":[65],"yielding":[67],"latent":[68],"that":[71,84,124,128],"can":[72],"support":[73],"both":[74],"tasks.":[80],"HDGL,":[81],"unlike":[82],"GNNs":[83],"rely":[85],"on":[86,116,140],"computationally":[87,159],"expensive":[88],"iterative":[89],"optimization":[90],"hyperparameter":[92],"tuning,":[93],"requires":[94],"only":[95],"single":[97],"pass":[98],"through":[99],"data":[101],"set.":[102],"report":[104],"results":[105],"experiments":[107],"widely":[109],"used":[110],"benchmark":[111],"datasets":[112],"which":[113],"demonstrate":[114],"that,":[115],"task,":[120,144],"achieves":[122],"accuracy":[123],"is":[125],"competitive":[126],"with":[127],"state-of-the-art":[131,161],"GNN":[132],"methods":[133],"at":[134],"substantially":[135],"reduced":[136],"computational":[137],"cost;":[138],"matches":[146],"performance":[148],"DeepWalk":[150],"related":[152],"methods,":[153],"although":[154],"it":[155],"falls":[156],"short":[157],"demanding":[160],"GNNs.":[162]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-04-12T07:58:50.170612","created_date":"2025-10-10T00:00:00"}