{"id":"https://openalex.org/W2116798331","doi":"https://doi.org/10.1109/ijcnn.2013.6707057","title":"Learning Bayesian Network leveled-structure from support based XML frequent itemsets","display_name":"Learning Bayesian Network leveled-structure from support based XML frequent itemsets","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2116798331","doi":"https://doi.org/10.1109/ijcnn.2013.6707057","mag":"2116798331"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2013.6707057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6707057","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","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/A5077101503","display_name":"Khalid Iqbal","orcid":"https://orcid.org/0000-0001-8877-7612"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Khalid Iqbal","raw_affiliation_strings":["Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China","Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]},{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China#TAB#","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074514262","display_name":"Xu-Cheng Yin","orcid":"https://orcid.org/0000-0003-0023-0220"},"institutions":[{"id":"https://openalex.org/I92403157","display_name":"University of Science and Technology Beijing","ror":"https://ror.org/02egmk993","country_code":"CN","type":"education","lineage":["https://openalex.org/I92403157"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu-Cheng Yin","raw_affiliation_strings":["Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China","Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China","institution_ids":["https://openalex.org/I92403157"]},{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology Beijing, Beijing, China#TAB#","institution_ids":["https://openalex.org/I92403157"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055393039","display_name":"Hongwei Hao","orcid":"https://orcid.org/0000-0003-2019-516X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong-Wei Hao","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China","Inst. of Autom., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Inst. of Autom., Beijing, China","institution_ids":["https://openalex.org/I4210094879"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025115747","display_name":"Qazi Mudassar Ilyas","orcid":"https://orcid.org/0000-0003-4238-8093"},"institutions":[{"id":"https://openalex.org/I4626487","display_name":"King Faisal University","ror":"https://ror.org/00dn43547","country_code":"SA","type":"education","lineage":["https://openalex.org/I4626487"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Qazi Mudassar Ilyas","raw_affiliation_strings":["College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia","College of Computer Science & Information Technology, King Faisal University, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia","institution_ids":["https://openalex.org/I4626487"]},{"raw_affiliation_string":"College of Computer Science & Information Technology, King Faisal University, Saudi Arabia","institution_ids":["https://openalex.org/I4626487"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5077101503"],"corresponding_institution_ids":["https://openalex.org/I92403157"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19766196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998000264167786,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9980000257492065,"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/computer-science","display_name":"Computer science","score":0.8083019256591797},{"id":"https://openalex.org/keywords/xml","display_name":"XML","score":0.699757993221283},{"id":"https://openalex.org/keywords/xml-database","display_name":"XML database","score":0.6222889423370361},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.6131198406219482},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5747560858726501},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.5486595630645752},{"id":"https://openalex.org/keywords/apriori-algorithm","display_name":"Apriori algorithm","score":0.5408244132995605},{"id":"https://openalex.org/keywords/efficient-xml-interchange","display_name":"Efficient XML Interchange","score":0.48175764083862305},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.41486018896102905},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.3381774425506592},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3314895033836365},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25786763429641724},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.06150484085083008}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8083019256591797},{"id":"https://openalex.org/C8797682","wikidata":"https://www.wikidata.org/wiki/Q2115","display_name":"XML","level":2,"score":0.699757993221283},{"id":"https://openalex.org/C183068750","wikidata":"https://www.wikidata.org/wiki/Q357393","display_name":"XML database","level":3,"score":0.6222889423370361},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6131198406219482},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5747560858726501},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.5486595630645752},{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.5408244132995605},{"id":"https://openalex.org/C11508877","wikidata":"https://www.wikidata.org/wiki/Q1124477","display_name":"Efficient XML Interchange","level":3,"score":0.48175764083862305},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.41486018896102905},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3381774425506592},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3314895033836365},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25786763429641724},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.06150484085083008},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2013.6707057","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2013.6707057","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"The 2013 International Joint Conference on Neural Networks (IJCNN)","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W159524162","https://openalex.org/W208128215","https://openalex.org/W1520720062","https://openalex.org/W1526335225","https://openalex.org/W1530964327","https://openalex.org/W1557997065","https://openalex.org/W1581468894","https://openalex.org/W1615454278","https://openalex.org/W1973996621","https://openalex.org/W1984071573","https://openalex.org/W2003411829","https://openalex.org/W2008906462","https://openalex.org/W2010780779","https://openalex.org/W2017102965","https://openalex.org/W2026562765","https://openalex.org/W2056801195","https://openalex.org/W2099753921","https://openalex.org/W2100125501","https://openalex.org/W2103012681","https://openalex.org/W2112614314","https://openalex.org/W2125531621","https://openalex.org/W2129714679","https://openalex.org/W2136891570","https://openalex.org/W2140190241","https://openalex.org/W2143945853","https://openalex.org/W2146112066","https://openalex.org/W2150673395","https://openalex.org/W2159795801","https://openalex.org/W2160233899","https://openalex.org/W2165190832","https://openalex.org/W2397866408","https://openalex.org/W2810926708","https://openalex.org/W4230160799","https://openalex.org/W4233413206","https://openalex.org/W4236354166","https://openalex.org/W6606471382","https://openalex.org/W6634656658","https://openalex.org/W6636455871","https://openalex.org/W6653095137","https://openalex.org/W6753307516"],"related_works":["https://openalex.org/W2390051172","https://openalex.org/W2297208791","https://openalex.org/W2367209111","https://openalex.org/W2351000793","https://openalex.org/W2366790077","https://openalex.org/W2348276166","https://openalex.org/W3034345083","https://openalex.org/W2607264580","https://openalex.org/W3012205960","https://openalex.org/W1483188779"],"abstract_inverted_index":{"XML":[0,17,25,29,33,41,64,71,98,110,136,153,159,179,203],"(eXtensible":[1],"Markup":[2],"Language)":[3],"is":[4,55,103,125,175,190,239],"a":[5,50,118,141],"standard":[6],"and":[7,13,131,139,207,225,247],"entirely":[8],"user-driven":[9],"language":[10],"for":[11,23],"storage":[12],"transfer":[14],"of":[15,49,57,75,81,91,97,109,129,150,165,185,202,235,245],"information.":[16],"frequent":[18,34,65,72,99,111,137,154,180,205],"itemsets":[19,35,66,73,138,155,161,206],"are":[20,156],"usually":[21],"found":[22,87,157],"mining":[24],"association":[26],"rules":[27],"from":[28,158],"transactional":[30],"databases.":[31],"These":[32],"lead":[36],"researchers":[37],"to":[38,62,105,134,197],"find":[39,135,208],"interesting":[40],"patterns":[42],"in":[43,192],"large":[44,204],"databases":[45],"with":[46,88,162,194],"the":[47,58,89,107,163,183,242],"use":[48,90,164],"threshold":[51],"value.":[52,70],"Apriori":[53,120],"algorithm":[54,102,124,189,196],"one":[56],"most":[59],"leading":[60],"solutions":[61],"discover":[63],"based":[67,177],"on":[68,178],"support":[69,166],"consist":[74],"similar":[76],"items":[77],"which":[78],"show":[79],"evidence":[80],"association.":[82],"This":[83,123],"relationship":[84,210],"can":[85],"be":[86],"Bayesian":[92,143,199],"Network":[93,144,200],"by":[94],"learning":[95,140,147,223],"structure":[96,108,201],"itemsets.":[100,112],"K2":[101,121,132,188,248],"used":[104,191],"learn":[106,198],"In":[113],"this":[114,151],"work,":[115],"we":[116],"propose":[117],"novel":[119,127],"algorithm.":[122,170,187],"composed":[126],"direction":[128],"apriori":[130,169,186,195,246],"algorithms":[133],"level-wise":[142],"structure.":[145],"For":[146],"each":[148,212],"level":[149],"structure,":[152],"candidate":[160],"measure":[167],"using":[168],"An":[171],"updated":[172],"binary":[173],"table":[174],"prepared":[176],"itemset":[181],"during":[182],"execution":[184],"conjunction":[193],"their":[209],"at":[211],"level.":[213],"We":[214],"have":[215,231],"extensively":[216],"tested":[217],"our":[218,236],"solution":[219,238],"over":[220],"UCI":[221],"machine":[222],"datasets":[224],"measured":[226],"its":[227],"performance.":[228],"The":[229],"results":[230],"shown":[232],"that":[233],"performance":[234,244],"proposed":[237],"better":[240],"than":[241],"combined":[243],"algorithms.":[249]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
