{"id":"https://openalex.org/W3175512679","doi":"https://doi.org/10.1145/3457682.3457715","title":"Inter-domain Link Inference with Confidence Using Na\u00efve Bayes Classifier","display_name":"Inter-domain Link Inference with Confidence Using Na\u00efve Bayes Classifier","publication_year":2021,"publication_date":"2021-02-26","ids":{"openalex":"https://openalex.org/W3175512679","doi":"https://doi.org/10.1145/3457682.3457715","mag":"3175512679"},"language":"en","primary_location":{"id":"doi:10.1145/3457682.3457715","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3457682.3457715","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 13th International Conference on Machine Learning and Computing","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/A5006385137","display_name":"Yi Zhao","orcid":"https://orcid.org/0000-0002-1152-1229"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yi Zhao","raw_affiliation_strings":["State Key Laboratory of Mathematical Engineering and Advanced Computing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mathematical Engineering and Advanced Computing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351112","display_name":"Yan Liu","orcid":"https://orcid.org/0000-0002-8257-2701"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan Liu","raw_affiliation_strings":["State Key Laboratory of Mathematical Engineering and Advanced Computing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mathematical Engineering and Advanced Computing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045937970","display_name":"Xiaoyu Guo","orcid":"https://orcid.org/0000-0002-0401-5723"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"XiaoYu Guo","raw_affiliation_strings":["State Key Laboratory of Mathematical Engineering and Advanced Computing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mathematical Engineering and Advanced Computing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087302367","display_name":"ZhongHang Sui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"ZhongHang Sui","raw_affiliation_strings":["State Key Laboratory of Mathematical Engineering and Advanced Computing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Mathematical Engineering and Advanced Computing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5006385137"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.09934201,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"217","last_page":"222"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9952999949455261,"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"}},"topics":[{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9952999949455261,"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"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9948999881744385,"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"}},{"id":"https://openalex.org/T12326","display_name":"Network Packet Processing and Optimization","score":0.9925000071525574,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7138690948486328},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6987393498420715},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.5301053524017334},{"id":"https://openalex.org/keywords/bayes-theorem","display_name":"Bayes' theorem","score":0.5241730213165283},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4838325083255768},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4732951521873474},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.471162885427475},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.437282532453537},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4361899793148041},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3540879487991333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7138690948486328},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6987393498420715},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.5301053524017334},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.5241730213165283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4838325083255768},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4732951521873474},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.471162885427475},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.437282532453537},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4361899793148041},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3540879487991333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3457682.3457715","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3457682.3457715","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 13th International Conference on Machine Learning and Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3291271152","display_name":null,"funder_award_id":"U1804263","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"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":15,"referenced_works":["https://openalex.org/W1514211162","https://openalex.org/W1532325895","https://openalex.org/W1583477060","https://openalex.org/W1996093955","https://openalex.org/W2018645873","https://openalex.org/W2044725071","https://openalex.org/W2063495160","https://openalex.org/W2152885278","https://openalex.org/W2171241196","https://openalex.org/W2294448035","https://openalex.org/W2554361663","https://openalex.org/W2555294241","https://openalex.org/W2559661823","https://openalex.org/W2900101584","https://openalex.org/W4213009331"],"related_works":["https://openalex.org/W2013493105","https://openalex.org/W2972991241","https://openalex.org/W2012610719","https://openalex.org/W2009699504","https://openalex.org/W1987909119","https://openalex.org/W235411870","https://openalex.org/W2381390841","https://openalex.org/W4237728685","https://openalex.org/W2089519699","https://openalex.org/W2122780970"],"abstract_inverted_index":{"Inter-domain":[0],"link":[1,44,48,68],"inference":[2],"is":[3,77,93,100,109],"not":[4],"only":[5],"important":[6],"for":[7,95],"network":[8,24],"security":[9],"and":[10,23,49,106,126],"fault":[11],"diagnosis,":[12],"but":[13],"also":[14],"helps":[15],"to":[16,79,103],"conduct":[17],"research":[18],"on":[19,29,128],"inter-domain":[20,50],"congestion":[21],"detection":[22],"resilience":[25],"assessment.":[26],"Current":[27],"researches":[28],"this":[30,40],"issue":[31],"lack":[32],"confidence":[33,111],"analysis":[34],"of":[35,66,82,88,112],"the":[36,42,55,62,83,104,107,110,113,129],"inferred":[37],"results.":[38],"In":[39,85],"paper,":[41],"IP":[43],"types":[45,69],"(i.e.,":[46],"intra-domain":[47],"link)":[51],"are":[52,64],"considered":[53],"as":[54],"latent":[56],"variable":[57],"in":[58],"probability":[59,108],"model,":[60],"while":[61],"parameters":[63,81],"probabilities":[65],"different":[67],"with":[70],"particular":[71],"features.":[72],"The":[73,97,115],"expectation":[74],"maximization":[75],"algorithm":[76],"applied":[78],"estimate":[80],"model.":[84],"each":[86],"iteration":[87],"EM":[89],"algorithm,":[90],"Na\u00efve":[91],"Bayes":[92],"used":[94],"classification.":[96],"final":[98],"result":[99],"determined":[101],"according":[102],"probability,":[105],"result.":[114],"experimental":[116],"results":[117],"show":[118],"that":[119],"our":[120],"method":[121],"can":[122],"achieve":[123],"better":[124],"precision":[125],"recall":[127],"validation":[130],"set":[131],"than":[132],"two":[133],"existing":[134],"general":[135],"methods.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}