{"id":"https://openalex.org/W4415125665","doi":"https://doi.org/10.1109/icnp65844.2025.11192381","title":"Towards Automatic Network Diagram Comprehension","display_name":"Towards Automatic Network Diagram Comprehension","publication_year":2025,"publication_date":"2025-09-22","ids":{"openalex":"https://openalex.org/W4415125665","doi":"https://doi.org/10.1109/icnp65844.2025.11192381"},"language":"en","primary_location":{"id":"doi:10.1109/icnp65844.2025.11192381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp65844.2025.11192381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 33rd International Conference on Network Protocols (ICNP)","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/A5058053289","display_name":"Yan-Yu Ren","orcid":"https://orcid.org/0000-0003-0594-0029"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyu Ren","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048781372","display_name":"Yukai Miao","orcid":"https://orcid.org/0000-0002-6401-5979"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yukai Miao","raw_affiliation_strings":["Zhongguancun Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhongguancun Laboratory","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100379227","display_name":"Li Chen","orcid":"https://orcid.org/0000-0002-2878-5351"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Chen","raw_affiliation_strings":["Zhongguancun Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhongguancun Laboratory","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380719","display_name":"Dan Li","orcid":"https://orcid.org/0000-0002-3426-3023"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Li","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xizheng Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xizheng Wang","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100706074","display_name":"Yu Bai","orcid":"https://orcid.org/0000-0002-7577-6001"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu Bai","raw_affiliation_strings":["Zhongguancun Laboratory"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhongguancun Laboratory","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113027774","display_name":"Zhiyuan Wu","orcid":"https://orcid.org/0009-0001-8016-5985"},"institutions":[{"id":"https://openalex.org/I4210125161","display_name":"International Center for Transitional Justice","ror":"https://ror.org/038a3t246","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210125161"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiyuan Wu","raw_affiliation_strings":["CAS,ICT"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CAS,ICT","institution_ids":["https://openalex.org/I4210125161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103488096","display_name":"Fei Long","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Long","raw_affiliation_strings":["Tsinghua University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24637531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9700999855995178,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9700999855995178,"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/T10679","display_name":"Service-Oriented Architecture and Web Services","score":0.9595999717712402,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9538999795913696,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6290000081062317},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5206000208854675},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4537000060081482},{"id":"https://openalex.org/keywords/debugging","display_name":"Debugging","score":0.43140000104904175},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.4221000075340271},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4180999994277954},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.41690000891685486},{"id":"https://openalex.org/keywords/network-analysis","display_name":"Network analysis","score":0.35339999198913574},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.33809998631477356}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7702000141143799},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6290000081062317},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5206000208854675},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4537000060081482},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4465000033378601},{"id":"https://openalex.org/C168065819","wikidata":"https://www.wikidata.org/wiki/Q845566","display_name":"Debugging","level":2,"score":0.43140000104904175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4300000071525574},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.4221000075340271},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4180999994277954},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.35339999198913574},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32820001244544983},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C17231256","wikidata":"https://www.wikidata.org/wiki/Q5156540","display_name":"Completeness (order theory)","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29580000042915344},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2872999906539917},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.2784999907016754},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C81877898","wikidata":"https://www.wikidata.org/wiki/Q1965787","display_name":"Network monitoring","level":2,"score":0.26579999923706055},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C186399060","wikidata":"https://www.wikidata.org/wiki/Q959962","display_name":"Diagram","level":2,"score":0.2551000118255615}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icnp65844.2025.11192381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icnp65844.2025.11192381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 33rd International Conference on Network Protocols (ICNP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1933349210","https://openalex.org/W1994022095","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2132022337","https://openalex.org/W2136451165","https://openalex.org/W2222512263","https://openalex.org/W2307512708","https://openalex.org/W2560730294","https://openalex.org/W2584723080","https://openalex.org/W2963351448","https://openalex.org/W2963839617","https://openalex.org/W2964241181","https://openalex.org/W3096609285","https://openalex.org/W3106074631","https://openalex.org/W3199003182","https://openalex.org/W4285294723","https://openalex.org/W4308623137","https://openalex.org/W4312933868","https://openalex.org/W4390023570","https://openalex.org/W4390874575","https://openalex.org/W4391590983","https://openalex.org/W4394946189","https://openalex.org/W4402753874"],"related_works":[],"abstract_inverted_index":{"Network":[0,88,211],"Diagram":[1],"Comprehension":[2],"(NDC)":[3],"is":[4,40],"a":[5,22,65,109,113,124,142,202],"vital":[6],"task":[7],"for":[8,145],"networking":[9,146],"professionals,":[10],"offering":[11],"essential":[12],"insights":[13],"into":[14],"network":[15,105,160],"topology":[16],"and":[17,53,68,75,98,101,119,137,140,162,195,197],"configurations.":[18],"However,":[19],"NDC":[20,46,62,155],"remains":[21],"labor-intensive":[23],"process":[24],"heavily":[25],"reliant":[26],"on":[27,207],"human":[28],"expertise,":[29],"with":[30,123,135,168],"existing":[31,186],"tools":[32],"falling":[33],"short":[34],"in":[35,55],"addressing":[36],"this":[37,81,149],"challenge.":[38],"It":[39],"critical":[41],"to":[42,72,96,116,131,172],"develop":[43,152],"an":[44,128],"Automatic":[45],"(ANDC)":[47],"system":[48,94],"that":[49,183],"ensures":[50],"high":[51],"faithfulness":[52,194],"completeness":[54],"information":[56,103],"extraction":[57],"while":[58],"supporting":[59],"practical,":[60],"end-to-end":[61],"applications.":[63],"Moreover,":[64],"comprehensive":[66],"dataset":[67],"benchmark":[69,171],"are":[70],"necessary":[71],"systematically":[73],"evaluate":[74,173],"drive":[76],"the":[77,91,169,208],"progress":[78],"of":[79,87],"ANDC.In":[80],"work,":[82],"we":[83,151],"introduce":[84],"Layered":[85],"Extractor":[86],"Diagrams":[89],"(LEND),":[90],"first":[92,170],"ANDC":[93,174],"designed":[95],"comprehensively":[97],"faithfully":[99],"extract":[100],"utilize":[102],"from":[104,164],"diagrams.":[106],"LEND":[107,184],"employs":[108],"three-stage":[110],"pipeline:":[111],"(1)":[112],"layer":[114],"extractor":[115],"decompose":[117],"diagrams":[118,161],"identify":[120],"key":[121],"elements":[122],"denoising":[125],"cascade,":[126],"(2)":[127],"inter-layer":[129],"combiner":[130],"reconstruct":[132],"entity":[133],"relations":[134],"positional":[136],"domain":[138],"knowledge,":[139],"(3)":[141],"task-specific":[143],"interpreter":[144],"applications.To":[147],"support":[148],"effort,":[150],"two":[153],"extensive":[154],"datasets":[156],"comprising":[157],"over":[158],"4,000":[159],"icons":[163],"diverse":[165],"sources,":[166],"along":[167],"systems":[175],"across":[176],"three":[177],"distinct":[178],"metrics.":[179],"Empirical":[180],"experiments":[181],"demonstrate":[182],"outperforms":[185],"methods":[187],"by":[188,205],"achieving":[189],"at":[190],"1.21\u2013":[191],"5.10\u00d7":[192],"better":[193],"completeness,":[196],"improves":[198],"its":[199],"capability":[200],"as":[201],"NetOps":[203],"engineer":[204],"30.5%":[206],"Cisco":[209],"Certified":[210],"Associate":[212],"(CCNA)":[213],"exam.":[214]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-14T00:00:00"}
