{"id":"https://openalex.org/W2556838012","doi":"https://doi.org/10.1109/tnnls.2016.2603784","title":"Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks","display_name":"Deep Logic Networks: Inserting and Extracting Knowledge From Deep Belief Networks","publication_year":2016,"publication_date":"2016-11-08","ids":{"openalex":"https://openalex.org/W2556838012","doi":"https://doi.org/10.1109/tnnls.2016.2603784","mag":"2556838012","pmid":"https://pubmed.ncbi.nlm.nih.gov/27845678"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2016.2603784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2603784","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Deep_Logic_Networks_Inserting_and_Extracting_Knowledge_From_Deep_Belief_Networks/28157390","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008915336","display_name":"Son N. Tran","orcid":"https://orcid.org/0000-0002-5912-293X"},"institutions":[{"id":"https://openalex.org/I180825142","display_name":"City, University of London","ror":"https://ror.org/04489at23","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I180825142"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Son N. Tran","raw_affiliation_strings":["Department of Computer Science, City University London, London, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University London, London, U.K","institution_ids":["https://openalex.org/I180825142"]}]},{"author_position":"last","author":{"id":null,"display_name":"Artur S. d'Avila Garcez","orcid":"https://orcid.org/0000-0002-6060-0409"},"institutions":[{"id":"https://openalex.org/I180825142","display_name":"City, University of London","ror":"https://ror.org/04489at23","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I180825142"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Artur S. d'Avila Garcez","raw_affiliation_strings":["Department of Computer Science, City University London, London, U.K"],"raw_orcid":"https://orcid.org/0000-0002-6060-0409","affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University London, London, U.K","institution_ids":["https://openalex.org/I180825142"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180825142"],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":14.8894,"has_fulltext":false,"cited_by_count":148,"citation_normalized_percentile":{"value":0.98715177,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"29","issue":"2","first_page":"246","last_page":"258"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9973000288009644,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9973000288009644,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9890999794006348,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9890000224113464,"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":0.5441438555717468},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5441161394119263},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.5222193002700806},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4977093040943146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5441438555717468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5441161394119263},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.5222193002700806},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4977093040943146}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tnnls.2016.2603784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2016.2603784","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:27845678","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/27845678","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":"Journal Article"},{"id":"pmh:oai:openaccess.city.ac.uk:19150","is_oa":false,"landing_page_url":"https://openaccess.city.ac.uk/view/creators_id/a=2Egarcez.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4306401940","display_name":"City Research Online (City University London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I180825142","host_organization_name":"City, University of London","host_organization_lineage":["https://openalex.org/I180825142"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:figshare.com:article/28157390","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Deep_Logic_Networks_Inserting_and_Extracting_Knowledge_From_Deep_Belief_Networks/28157390","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/28157390","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Deep_Logic_Networks_Inserting_and_Extracting_Knowledge_From_Deep_Belief_Networks/28157390","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W142185896","https://openalex.org/W1508395088","https://openalex.org/W1510073064","https://openalex.org/W1526328753","https://openalex.org/W1531084120","https://openalex.org/W1538134818","https://openalex.org/W1585529040","https://openalex.org/W1599216479","https://openalex.org/W1670845525","https://openalex.org/W1813659000","https://openalex.org/W1860880244","https://openalex.org/W1958932515","https://openalex.org/W1968970479","https://openalex.org/W1969323767","https://openalex.org/W1977970897","https://openalex.org/W1989789052","https://openalex.org/W1990088911","https://openalex.org/W2004025832","https://openalex.org/W2005530747","https://openalex.org/W2034978228","https://openalex.org/W2036368940","https://openalex.org/W2046670074","https://openalex.org/W2065204741","https://openalex.org/W2084341220","https://openalex.org/W2095739681","https://openalex.org/W2099939455","https://openalex.org/W2100066980","https://openalex.org/W2103052024","https://openalex.org/W2110798204","https://openalex.org/W2112796928","https://openalex.org/W2116064496","https://openalex.org/W2116767760","https://openalex.org/W2130325614","https://openalex.org/W2133257461","https://openalex.org/W2136922672","https://openalex.org/W2147800946","https://openalex.org/W2154125551","https://openalex.org/W2159727905","https://openalex.org/W2165644552","https://openalex.org/W2209103479","https://openalex.org/W4244296837","https://openalex.org/W4300668030","https://openalex.org/W6605753235","https://openalex.org/W6638304892","https://openalex.org/W6674789083","https://openalex.org/W6676481782","https://openalex.org/W6679718588","https://openalex.org/W6684671274"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W3009238340","https://openalex.org/W2939353110","https://openalex.org/W4321369474","https://openalex.org/W4360585206","https://openalex.org/W1530536511","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W2248239756"],"abstract_inverted_index":{"Developments":[0],"in":[1,124,157],"deep":[2,23,58,78,125,161,170,185,194],"learning":[3,11,15,38,64],"have":[4],"seen":[5,27],"the":[6,52,72,89,119,158,165,177,188,202,209],"use":[7,99,189,210],"of":[8,54,74,88,105,121,160,169,179,184,190,211],"layerwise":[9,20,141,151],"unsupervised":[10],"combined":[12],"with":[13,201],"supervised":[14],"for":[16,118,140,176],"fine-tuning.":[17],"With":[18,187],"this":[19,41,96,191],"approach,":[21],"a":[22,29,85,100,137,173,193],"network":[24,221],"can":[25,48,62,83,135,153,217],"be":[26,49,218],"as":[28],"more":[30],"modular":[31],"system":[32,196],"that":[33,108,114,132,150,206],"lends":[34],"itself":[35],"well":[36],"to":[37,51,71,220],"representations.":[39],"In":[40],"paper,":[42],"we":[43,98,109],"investigate":[44],"whether":[45,60,81],"such":[46,93],"modularity":[47,207],"useful":[50],"insertion":[53,178,216],"background":[55],"knowledge":[56,75,130,181,215],"into":[57],"networks,":[59,79],"it":[61,67,82,115],"improve":[63],"performance":[65],"when":[66],"is":[68,116,197],"available,":[69],"and":[70,80,182,199,214],"extraction":[73,131,152],"from":[76],"trained":[77],"offer":[84,136],"better":[86],"understanding":[87],"representations":[90],"learned":[91],"by":[92,129],"networks.":[94,126,163,186],"To":[95],"end,":[97],"simple":[101],"symbolic":[102,167],"language-a":[103],"set":[104],"logical":[106],"rules":[107,134,213],"call":[110],"confidence":[111,133,212],"rules-and":[112],"show":[113,128,149],"suitable":[117],"representation":[120,139],"quantitative":[122],"reasoning":[123],"We":[127,147],"low-cost":[138],"networks":[142,171],"(or":[143],"restricted":[144],"Boltzmann":[145],"machines).":[146],"also":[148],"produce":[154],"an":[155],"improvement":[156],"accuracy":[159],"belief":[162],"Furthermore,":[164],"proposed":[166,198],"characterization":[168],"provides":[172],"novel":[174],"method":[175],"prior":[180],"training":[183],"method,":[192],"neural-symbolic":[195],"evaluated,":[200],"experimental":[203],"results":[204],"indicating":[205],"through":[208],"beneficial":[219],"performance.":[222]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":16},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":22},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":29},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3}],"updated_date":"2026-09-02T18:50:13.731487","created_date":"2025-10-10T00:00:00"}