{"id":"https://openalex.org/W4388040426","doi":"https://doi.org/10.1109/mlcad58807.2023.10299869","title":"Hybrid Utilization of Subgraph Isomorphism and Relational Graph Convolutional Networks for Analog Functional Grouping Annotation","display_name":"Hybrid Utilization of Subgraph Isomorphism and Relational Graph Convolutional Networks for Analog Functional Grouping Annotation","publication_year":2023,"publication_date":"2023-09-10","ids":{"openalex":"https://openalex.org/W4388040426","doi":"https://doi.org/10.1109/mlcad58807.2023.10299869"},"language":"en","primary_location":{"id":"doi:10.1109/mlcad58807.2023.10299869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlcad58807.2023.10299869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 ACM/IEEE 5th Workshop on Machine Learning for CAD (MLCAD)","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/A5090272656","display_name":"Zhengfeng Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengfeng Wu","raw_affiliation_strings":["Drexel University,Philadelphia,PA,USA","Drexel University, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Drexel University,Philadelphia,PA,USA","institution_ids":["https://openalex.org/I72816309"]},{"raw_affiliation_string":"Drexel University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I72816309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049693453","display_name":"Isabel Song","orcid":null},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Isabel Song","raw_affiliation_strings":["University of Pennsylvania,Philadelphia,PA,USA","University of Pennsylvania, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania,Philadelphia,PA,USA","institution_ids":["https://openalex.org/I79576946"]},{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059641297","display_name":"Ioannis Savidis","orcid":"https://orcid.org/0000-0003-4230-1795"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ioannis Savidis","raw_affiliation_strings":["Drexel University,Philadelphia,PA,USA","Drexel University, Philadelphia, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Drexel University,Philadelphia,PA,USA","institution_ids":["https://openalex.org/I72816309"]},{"raw_affiliation_string":"Drexel University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I72816309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.3269,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.95973882,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11522","display_name":"VLSI and FPGA Design Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/T14117","display_name":"Integrated Circuits and Semiconductor Failure Analysis","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6816406846046448},{"id":"https://openalex.org/keywords/subgraph-isomorphism-problem","display_name":"Subgraph isomorphism problem","score":0.6296306848526001},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5258346796035767},{"id":"https://openalex.org/keywords/hybrid-functional","display_name":"Hybrid functional","score":0.4608030319213867},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4499194025993347},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4253849387168884},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39123106002807617},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3627518117427826},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3205986022949219},{"id":"https://openalex.org/keywords/density-functional-theory","display_name":"Density functional theory","score":0.12669050693511963}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6816406846046448},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.6296306848526001},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5258346796035767},{"id":"https://openalex.org/C22693506","wikidata":"https://www.wikidata.org/wiki/Q3075290","display_name":"Hybrid functional","level":3,"score":0.4608030319213867},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4499194025993347},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4253849387168884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39123106002807617},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3627518117427826},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3205986022949219},{"id":"https://openalex.org/C152365726","wikidata":"https://www.wikidata.org/wiki/Q1048589","display_name":"Density functional theory","level":2,"score":0.12669050693511963},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlcad58807.2023.10299869","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlcad58807.2023.10299869","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 ACM/IEEE 5th Workshop on Machine Learning for CAD (MLCAD)","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":17,"referenced_works":["https://openalex.org/W1556472513","https://openalex.org/W1996605065","https://openalex.org/W2114912418","https://openalex.org/W2144133630","https://openalex.org/W2147405597","https://openalex.org/W2162637605","https://openalex.org/W2184826174","https://openalex.org/W3013793321","https://openalex.org/W3036312847","https://openalex.org/W3084745515","https://openalex.org/W3108107800","https://openalex.org/W3112236443","https://openalex.org/W3127378783","https://openalex.org/W3186013690","https://openalex.org/W3213645510","https://openalex.org/W4232735308","https://openalex.org/W4385679829"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2532922352","https://openalex.org/W2358755282","https://openalex.org/W2604893261","https://openalex.org/W2625833328","https://openalex.org/W2143195194"],"abstract_inverted_index":{"A":[0],"hybrid":[1,73,142,169,186,199],"method":[2],"is":[3,45,55,78,135,188],"proposed":[4,46,72,198],"that":[5,47,100,111,144],"combines":[6],"the":[7,21,33,38,59,71,75,84,138,148,168,172,185,194,197],"subgraph":[8],"isomorphism":[9],"algorithm":[10],"VF2":[11,116,146,162],"and":[12,23,82,107,219],"a":[13,41,64,95,102,118,158],"relational":[14],"graph":[15,43],"convolutional":[16],"network":[17],"(RGCN)":[18],"model":[19,54,77,150],"for":[20,212,229],"recognition":[22],"classification":[24],"of":[25,63,97,104,121,133,156,176,184,196,214],"functional":[26,65,85,109,126,174,204,221],"pairs":[27,86,110,205],"in":[28,152,201,206,233],"an":[29,128,153],"analog":[30,203,208],"circuit":[31,235],"at":[32],"device":[34],"level.":[35],"To":[36],"apply":[37],"RGCN":[39,53,76,149],"model,":[40],"heterogeneous":[42],"representation":[44],"includes":[48],"ten":[49],"edge":[50],"types.":[51],"The":[52,90,141,180,191,217],"trained":[56],"to":[57,80],"predict":[58],"presence":[60],"or":[61],"absence":[62],"pairing":[66],"between":[67],"two":[68],"transistors.":[69],"With":[70],"approach,":[74],"utilized":[79,232],"filter":[81],"label":[83],"returned":[87],"by":[88],"VF2.":[89],"techniques":[91],"are":[92,112],"characterized":[93],"on":[94],"dataset":[96],"14":[98],"circuits":[99],"include":[101],"total":[103],"219":[105],"transistors":[106],"120":[108,125],"manually":[113],"annotated.":[114],"While":[115],"achieves":[117],"perfect":[119],"recall":[120],"1,":[122],"recognizing":[123],"all":[124],"pairs,":[127],"average":[129,181],"false":[130],"positive":[131],"rate":[132],"35.9%":[134],"observed":[136],"among":[137],"detected":[139,178,218],"pairs.":[140],"approach":[143,170,187,200],"integrates":[145],"with":[147],"results":[151,192],"F1":[154],"score":[155],"0.882,":[157],"14.4%":[159],"improvement":[160],"over":[161],"when":[163],"executed":[164],"alone.":[165],"In":[166],"addition,":[167],"returns":[171],"specific":[173],"type":[175],"each":[177],"pair.":[179],"execution":[182],"time":[183],"0.594":[189],"seconds.":[190],"confirm":[193],"effectiveness":[195],"detecting":[202],"practical":[207],"EDA":[209],"applications":[210],"including":[211],"annotation":[213],"symmetry":[215],"constraints.":[216],"labeled":[220],"pair":[222],"types":[223],"also":[224],"provide":[225],"utility":[226],"as":[227],"features":[228],"learning":[230],"models":[231],"additional":[234],"applications.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}