{"id":"https://openalex.org/W4312452452","doi":"https://doi.org/10.1109/bigdataservice55688.2022.00022","title":"Active Learning for Node Classification using a Convex Optimization approach","display_name":"Active Learning for Node Classification using a Convex Optimization approach","publication_year":2022,"publication_date":"2022-08-01","ids":{"openalex":"https://openalex.org/W4312452452","doi":"https://doi.org/10.1109/bigdataservice55688.2022.00022"},"language":"en","primary_location":{"id":"doi:10.1109/bigdataservice55688.2022.00022","doi":"https://doi.org/10.1109/bigdataservice55688.2022.00022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdataservice55688.2022.00022","pdf_url":null,"source":{"id":"https://openalex.org/S7407088894","display_name":"IEEE International Conference on Big Data Computing Service and Applications (BigDataService)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Eighth International Conference on Big Data Computing Service and Applications (BigDataService)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5051695162","display_name":"Deepesh Agarwal","orcid":"https://orcid.org/0000-0001-5874-043X","observed_orcids":["https://orcid.org/0000-0001-5874-043X"]},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deepesh Agarwal","raw_affiliation_strings":["Kansas State University,Department of Electrical and Computer Engineering,Manhattan,Kansas,USA","Department of Electrical and Computer Engineering, Kansas State University, Manhattan, Kansas, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kansas State University,Department of Electrical and Computer Engineering,Manhattan,Kansas,USA","institution_ids":["https://openalex.org/I189590672"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Kansas State University, Manhattan, Kansas, USA","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003778401","display_name":"Balasubramaniam Natarajan","orcid":"https://orcid.org/0000-0001-6429-9003","observed_orcids":["https://orcid.org/0000-0001-6429-9003"]},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Balasubramaniam Natarajan","raw_affiliation_strings":["Kansas State University,Department of Electrical and Computer Engineering,Manhattan,Kansas,USA","Department of Electrical and Computer Engineering, Kansas State University, Manhattan, Kansas, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kansas State University,Department of Electrical and Computer Engineering,Manhattan,Kansas,USA","institution_ids":["https://openalex.org/I189590672"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Kansas State University, Manhattan, Kansas, USA","institution_ids":["https://openalex.org/I189590672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I189590672"],"apc_list":null,"apc_paid":null,"fwci":0.4191,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.5764607,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"96","last_page":"102"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.7968999743461609,"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":0.7968999743461609,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.19580000638961792,"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":0.001500000013038516,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/active-learning-machine-learning","display_name":"active learning (machine learning)","score":0.9990000128746033},{"id":"https://openalex.org/keywords/node-classification","display_name":"node classification","score":0.875},{"id":"https://openalex.org/keywords/graph-neural-networks","display_name":"graph neural networks","score":0.9940000176429749},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"convex optimization","score":0.7549999952316284},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"semi-supervised learning","score":0.7839999794960022},{"id":"https://openalex.org/keywords/attributed-networks","display_name":"attributed graphs","score":0.968999981880188},{"id":"https://openalex.org/keywords/graph-centrality-measures","display_name":"graph centrality","score":0.6710000038146973},{"id":"https://openalex.org/keywords/graph-data","display_name":"graph data","score":0.40700000524520874}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7573546171188354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.598468005657196},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.5839162468910217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.564452052116394},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4618948698043823},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4516729712486267},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4345037043094635},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41652870178222656},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3103209435939789},{"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdataservice55688.2022.00022","doi":"https://doi.org/10.1109/bigdataservice55688.2022.00022","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdataservice55688.2022.00022","pdf_url":null,"source":{"id":"https://openalex.org/S7407088894","display_name":"IEEE International Conference on Big Data Computing Service and Applications (BigDataService)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Eighth International Conference on Big Data Computing Service and Applications (BigDataService)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1642010679","https://openalex.org/W2017803598","https://openalex.org/W2116341502","https://openalex.org/W2132022337","https://openalex.org/W2138002832","https://openalex.org/W2139823104","https://openalex.org/W2143387805","https://openalex.org/W2153959628","https://openalex.org/W2154455818","https://openalex.org/W2167828456","https://openalex.org/W2168190036","https://openalex.org/W2173027866","https://openalex.org/W2244807774","https://openalex.org/W2290847742","https://openalex.org/W2468907370","https://openalex.org/W2519887557","https://openalex.org/W2552391307","https://openalex.org/W2606780347","https://openalex.org/W2624431344","https://openalex.org/W2624614404","https://openalex.org/W2766453196","https://openalex.org/W2788919350","https://openalex.org/W2804057010","https://openalex.org/W2804180102","https://openalex.org/W2808130788","https://openalex.org/W2811124557","https://openalex.org/W2903158431","https://openalex.org/W2946721323","https://openalex.org/W2970971581","https://openalex.org/W3093309692","https://openalex.org/W3212130749","https://openalex.org/W4244364296"],"related_works":["https://openalex.org/W2981275410","https://openalex.org/W4205247958","https://openalex.org/W4226077070","https://openalex.org/W7054916877","https://openalex.org/W3093309692","https://openalex.org/W7216822173","https://openalex.org/W4307725081","https://openalex.org/W3095454939","https://openalex.org/W2969471275","https://openalex.org/W3034524878"],"abstract_inverted_index":{"The":[0,69,99,145,163],"recent":[1],"advancements":[2],"related":[3],"to":[4,31,115,181],"big":[5],"data":[6,33,49,55,73],"analytics":[7],"in":[8,35,51,142,184],"the":[9,32,78,121,128,169],"era":[10],"of":[11,20,71,96,101,108,140],"Industry":[12],"4.0":[13],"are":[14,44,56,88],"fueled":[15],"by":[16,119,155,187],"development":[17],"and":[18,64,83,94,174],"deployment":[19],"decision":[21],"models":[22,104],"based":[23],"on":[24,77],"neural":[25],"network":[26],"(NN)":[27],"architectures.":[28],"In":[29],"addition":[30],"represented":[34,58],"Euclidean":[36],"space,":[37],"like,":[38],"images,":[39],"text,":[40],"or":[41],"videos,":[42],"there":[43],"increasing":[45],"applications":[46],"which":[47],"demand":[48],"representation":[50],"non-Euclidean":[52],"domains.":[53],"Such":[54],"typically":[57],"as":[59,150,177],"graphs":[60],"with":[61,135],"complex":[62],"interactions":[63],"interdependencies":[65],"between":[66],"various":[67],"entities.":[68],"complexity":[70],"graph":[72],"imposes":[74],"substantial":[75],"challenge":[76],"traditional":[79],"Deep":[80],"NN":[81],"models,":[82],"Graph":[84],"Neural":[85],"Networks":[86],"(GNN)":[87],"a":[89,151],"powerful":[90],"extension":[91],"for":[92,125,137],"modeling":[93],"analysis":[95],"networked":[97],"data.":[98,110],"training":[100,129],"these":[102],"computational":[103],"requires":[105],"large":[106],"amounts":[107],"labeled":[109],"Active":[111],"Learning":[112],"(AL)":[113],"helps":[114],"overcome":[116],"this":[117],"issue":[118],"selecting":[120],"most":[122],"informative":[123],"instances":[124],"labeling":[126],"during":[127],"process.":[130],"This":[131],"paper":[132],"combines":[133],"AL":[134,146,178],"GNN":[136],"semi-supervised":[138],"classification":[139,185],"nodes":[141],"attributed":[143],"graphs.":[144],"framework":[147],"is":[148],"portrayed":[149],"convex":[152],"optimization":[153],"problem":[154],"employing":[156],"Dissimilarity-based":[157],"Sparse":[158],"Modeling":[159],"Representative":[160],"Selection":[161],"(DSMRS).":[162],"experimental":[164],"evaluation":[165],"demonstrates":[166],"that":[167],"using":[168],"selected":[170],"graph-specific":[171],"metrics":[172],"(centrality":[173],"robustness":[175],"measures)":[176],"heuristics":[179],"leads":[180],"an":[182],"improvement":[183],"performance":[186],"upto":[188],"10%.":[189]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2023-01-04T00:00:00"}