{"id":"https://openalex.org/W4392942182","doi":"https://doi.org/10.1109/icmla58977.2023.00198","title":"Novel Representation Learning Technique Using Graphs for Performance Analytics","display_name":"Novel Representation Learning Technique Using Graphs for Performance Analytics","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4392942182","doi":"https://doi.org/10.1109/icmla58977.2023.00198"},"language":"en","primary_location":{"id":"doi:10.1109/icmla58977.2023.00198","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla58977.2023.00198","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Machine Learning and Applications (ICMLA)","raw_type":"proceedings-article"},"type":"article","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/A5058282095","display_name":"Tarek Ramadan","orcid":"https://orcid.org/0000-0002-6489-7668"},"institutions":[{"id":"https://openalex.org/I1342911587","display_name":"Oracle (United States)","ror":"https://ror.org/006c77m33","country_code":"US","type":"company","lineage":["https://openalex.org/I1342911587"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tarek Ramadan","raw_affiliation_strings":["Oracle Corporation"],"affiliations":[{"raw_affiliation_string":"Oracle Corporation","institution_ids":["https://openalex.org/I1342911587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093766677","display_name":"Ankur Lahiry","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ankur Lahiry","raw_affiliation_strings":["Texas State University"],"affiliations":[{"raw_affiliation_string":"Texas State University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002465410","display_name":"Tanzima Islam","orcid":"https://orcid.org/0000-0003-2877-5871"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tanzima Z. Islam","raw_affiliation_strings":["Texas State University"],"affiliations":[{"raw_affiliation_string":"Texas State University","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5058282095"],"corresponding_institution_ids":["https://openalex.org/I1342911587"],"apc_list":null,"apc_paid":null,"fwci":0.5545,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.78248288,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1311","last_page":"1318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.7889000177383423,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11122","display_name":"Online Learning and Analytics","score":0.7889000177383423,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.7464250326156616},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5527999997138977},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5411897897720337},{"id":"https://openalex.org/keywords/learning-analytics","display_name":"Learning analytics","score":0.43992286920547485},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3944852352142334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38980716466903687},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3499264121055603},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34822553396224976}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7464250326156616},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5527999997138977},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5411897897720337},{"id":"https://openalex.org/C2777648619","wikidata":"https://www.wikidata.org/wiki/Q2845208","display_name":"Learning analytics","level":2,"score":0.43992286920547485},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3944852352142334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38980716466903687},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3499264121055603},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34822553396224976},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmla58977.2023.00198","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmla58977.2023.00198","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Machine Learning and Applications (ICMLA)","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":51,"referenced_works":["https://openalex.org/W60493759","https://openalex.org/W125869453","https://openalex.org/W1522301498","https://openalex.org/W1961284565","https://openalex.org/W2005660937","https://openalex.org/W2101234009","https://openalex.org/W2116341502","https://openalex.org/W2132022337","https://openalex.org/W2145680191","https://openalex.org/W2166019559","https://openalex.org/W2296691800","https://openalex.org/W2337228275","https://openalex.org/W2340816002","https://openalex.org/W2601243251","https://openalex.org/W2604662567","https://openalex.org/W2727949054","https://openalex.org/W2756568380","https://openalex.org/W2896457183","https://openalex.org/W2949676527","https://openalex.org/W2970896257","https://openalex.org/W2980116950","https://openalex.org/W2988833907","https://openalex.org/W2997574889","https://openalex.org/W2998139906","https://openalex.org/W3080555959","https://openalex.org/W3120740533","https://openalex.org/W3124590480","https://openalex.org/W3129684848","https://openalex.org/W3170657538","https://openalex.org/W3174086521","https://openalex.org/W3176943960","https://openalex.org/W3193425397","https://openalex.org/W4252637763","https://openalex.org/W4287868418","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4399647672","https://openalex.org/W6631190155","https://openalex.org/W6681096077","https://openalex.org/W6703177460","https://openalex.org/W6703970976","https://openalex.org/W6738964360","https://openalex.org/W6747798010","https://openalex.org/W6755207826","https://openalex.org/W6771847183","https://openalex.org/W6773823057","https://openalex.org/W6781932242","https://openalex.org/W6799866547","https://openalex.org/W6869608176","https://openalex.org/W6908812986","https://openalex.org/W6910546390"],"related_works":["https://openalex.org/W1987827786","https://openalex.org/W2799586942","https://openalex.org/W2504091800","https://openalex.org/W2331775400","https://openalex.org/W2816728186","https://openalex.org/W2768832457","https://openalex.org/W2804624249","https://openalex.org/W2560130217","https://openalex.org/W605203981","https://openalex.org/W2911048623"],"abstract_inverted_index":{"The":[0],"performance":[1,85],"analytics":[2],"domain":[3],"in":[4,99,155,228],"High":[5],"Performance":[6],"Computing":[7],"(HPC)":[8],"uses":[9],"tabular":[10,33,84],"data":[11,86],"to":[12,89,109,126,185,198,222],"solve":[13],"regression":[14,182],"problems,":[15],"such":[16,114],"as":[17,115],"predicting":[18],"the":[19,28,37,50,53,91,118,142,150,153,156,160,163,232],"execution":[20],"time.":[21],"Existing":[22],"Machine":[23,240],"Learning":[24,241],"(ML)":[25],"techniques":[26,98],"leverage":[27,90],"correlations":[29],"among":[30],"features":[31,48,104,154],"given":[32],"datasets,":[34],"not":[35,121],"leveraging":[36],"relationships":[38,102],"between":[39,103,152],"samples":[40],"directly.":[41],"Moreover,":[42],"since":[43],"high-quality":[44],"embed-dings":[45],"from":[46,166],"raw":[47],"improve":[49],"fidelity":[51],"of":[52,82,93,162],"downstream":[54],"predictive":[55],"models,":[56],"existing":[57],"methods":[58,136],"rely":[59],"on":[60,149,169],"extensive":[61],"feature":[62],"engineering":[63],"and":[64,69,105,141,213,219,239],"pre-processing":[65],"steps,":[66],"costing":[67],"time":[68],"manual":[70],"effort.":[71],"To":[72,129],"fill":[73],"these":[74],"two":[75],"gaps,":[76],"we":[77,124,133],"propose":[78,134],"a":[79,175],"novel":[80],"idea":[81],"transforming":[83],"into":[87],"graphs":[88],"advancement":[92],"Graph":[94],"Neural":[95,215],"Network-based":[96],"(GNN)":[97],"capturing":[100],"complex":[101],"samples.":[106,157],"In":[107],"contrast":[108],"other":[110,186],"ML":[111],"application":[112],"domains,":[113],"social":[116],"networks,":[117],"graph":[119,212],"is":[120],"given;":[122],"instead,":[123],"need":[125],"build":[127],"it.":[128],"address":[130],"this":[131],"gap,":[132],"graph-building":[135],"where":[137],"nodes":[138],"represent":[139],"samples,":[140],"edges":[143],"are":[144],"automatically":[145],"inferred":[146],"iteratively":[147],"based":[148,168],"similarity":[151],"We":[158],"evaluate":[159],"effectiveness":[161],"generated":[164],"embeddings":[165],"GNNs":[167],"how":[170],"well":[171],"they":[172],"make":[173],"even":[174,195],"simple":[176],"feed-forward":[177],"neural":[178],"network":[179],"perform":[180],"for":[181,204,236],"tasks":[183],"compared":[184],"state-of-the-art":[187],"representation":[188],"learning":[189],"techniques.":[190],"Our":[191],"evaluation":[192],"demonstrates":[193],"that":[194],"with":[196],"up":[197,221],"25":[199],"%":[200,226],"random":[201],"missing":[202],"values":[203],"each":[205],"dataset,":[206],"our":[207],"method":[208],"outperforms":[209],"commonly":[210],"used":[211],"Deep":[214],"Network":[216],"(DNN)-based":[217],"approaches":[218],"achieves":[220],"61.67%":[223],"&":[224],"78.56":[225],"improvement":[227],"MSE":[229],"loss":[230],"over":[231],"DNN":[233],"baseline":[234],"respectively":[235],"HPC":[237],"dataset":[238],"Datasets.":[242]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}