{"id":"https://openalex.org/W290413992","doi":null,"title":"Interpreting Bayesian Logic Programs","display_name":"Interpreting Bayesian Logic Programs","publication_year":2000,"publication_date":"2000-01-01","ids":{"openalex":"https://openalex.org/W290413992","mag":"290413992"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.18.3662","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.3662","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.informatik.uni-freiburg.de/~kersting/aaai_srl_2000.ps.gz","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5037636074","display_name":"Kristian Kersting","orcid":"https://orcid.org/0000-0002-2873-9152","observed_orcids":["https://orcid.org/0000-0002-2873-9152"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kristian Kersting","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078136609","display_name":"Luc De Raedt","orcid":"https://orcid.org/0000-0002-6860-6303","observed_orcids":["https://orcid.org/0000-0002-6860-6303"]},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Luc De Raedt","raw_affiliation_strings":["Albert-Ludwigs-University of Freiburg"],"raw_orcid":"https://orcid.org/0000-0002-6860-6303","affiliations":[{"raw_affiliation_string":"Albert-Ludwigs-University of Freiburg","institution_ids":["https://openalex.org/I161046081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006247481","display_name":"Stefan Kr\u00e4mer","orcid":"https://orcid.org/0000-0002-0071-9344","observed_orcids":["https://orcid.org/0000-0002-0071-9344"]},"institutions":[{"id":"https://openalex.org/I161046081","display_name":"University of Freiburg","ror":"https://ror.org/0245cg223","country_code":"DE","type":"education","lineage":["https://openalex.org/I161046081"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Kr\u00e4mer","raw_affiliation_strings":["Albert-Ludwigs-University of Freiburg"],"raw_orcid":"https://orcid.org/0000-0002-0071-9344","affiliations":[{"raw_affiliation_string":"Albert-Ludwigs-University of Freiburg","institution_ids":["https://openalex.org/I161046081"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1892,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.91399608,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9761000275611877,"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":0.9761000275611877,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.023099999874830246,"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/T11596","display_name":"Constraint Satisfaction and Optimization","score":9.999999747378752e-05,"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/bayesian-networks","display_name":"Bayesian networks","score":0.9959999918937683},{"id":"https://openalex.org/keywords/probabilistic-logic-programming","display_name":"probabilistic logic programming","score":0.7649999856948853},{"id":"https://openalex.org/keywords/reasoning-under-uncertainty","display_name":"uncertainty reasoning","score":0.7480000257492065},{"id":"https://openalex.org/keywords/random-variable","display_name":"random variables","score":0.6230000257492065}],"concepts":[{"id":"https://openalex.org/C81721847","wikidata":"https://www.wikidata.org/wiki/Q163468","display_name":"Prolog","level":2,"score":0.7905232310295105},{"id":"https://openalex.org/C189790780","wikidata":"https://www.wikidata.org/wiki/Q933932","display_name":"Horn clause","level":3,"score":0.7049872875213623},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5946484804153442},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.5736210346221924},{"id":"https://openalex.org/C128838566","wikidata":"https://www.wikidata.org/wiki/Q275603","display_name":"Logic programming","level":2,"score":0.5297428369522095},{"id":"https://openalex.org/C127043819","wikidata":"https://www.wikidata.org/wiki/Q16243608","display_name":"Bayesian programming","level":5,"score":0.4942765235900879},{"id":"https://openalex.org/C97169998","wikidata":"https://www.wikidata.org/wiki/Q1582738","display_name":"Definite clause grammar","level":5,"score":0.4518886208534241},{"id":"https://openalex.org/C18998212","wikidata":"https://www.wikidata.org/wiki/Q7246856","display_name":"Probabilistic logic network","level":5,"score":0.4305284321308136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4142535328865051},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39032310247421265},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3822738528251648},{"id":"https://openalex.org/C102993220","wikidata":"https://www.wikidata.org/wiki/Q387196","display_name":"Description logic","level":2,"score":0.28365564346313477},{"id":"https://openalex.org/C203659156","wikidata":"https://www.wikidata.org/wiki/Q6934805","display_name":"Multimodal logic","level":3,"score":0.2675091028213501},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.265342116355896},{"id":"https://openalex.org/C3845977","wikidata":"https://www.wikidata.org/wiki/Q4826262","display_name":"Autoepistemic logic","level":4,"score":0.2556614875793457},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.18881851434707642},{"id":"https://openalex.org/C97212296","wikidata":"https://www.wikidata.org/wiki/Q338047","display_name":"Context-free grammar","level":3,"score":0.1335052251815796},{"id":"https://openalex.org/C29184939","wikidata":"https://www.wikidata.org/wiki/Q1134367","display_name":"Phrase structure grammar","level":4,"score":0.11205103993415833},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.07765501737594604}],"mesh":[],"locations_count":5,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.18.3662","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.18.3662","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.informatik.uni-freiburg.de/~kersting/aaai_srl_2000.ps.gz","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.25.2452","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.25.2452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://robotics.stanford.edu/srl/Papers/KKersting00.ps","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.333.5209","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.333.5209","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aaai.org/Papers/Workshops/2000/WS-00-06/WS00-06-005.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.342.3679","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.342.3679","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://arxiv.org/pdf/cs/0111058v1.pdf","raw_type":"text"},{"id":"mag:290413992","doi":null,"is_oa":false,"landing_page_url":"https://www.aaai.org/Papers/Workshops/2000/WS-00-06/WS00-06-005.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W61686890","https://openalex.org/W568057840","https://openalex.org/W1482998326","https://openalex.org/W1515653062","https://openalex.org/W1608748481","https://openalex.org/W1961449491","https://openalex.org/W1979667681","https://openalex.org/W1987902506","https://openalex.org/W2023578426","https://openalex.org/W2122410182","https://openalex.org/W2126151607","https://openalex.org/W2914587038"],"related_works":["https://openalex.org/W1723714545","https://openalex.org/W1028335124","https://openalex.org/W2543749952","https://openalex.org/W7098241065","https://openalex.org/W170725206","https://openalex.org/W1538192045","https://openalex.org/W2177977456","https://openalex.org/W7125230540","https://openalex.org/W7096446081","https://openalex.org/W7096444027"],"abstract_inverted_index":{"Bayesian":[0,47,50,66,86,98,113,118],"networks":[1,67,119],"provide":[2],"an":[3],"elegant":[4],"formalism":[5],"for":[6],"representing":[7],"and":[8,40,62,80,97,106],"reasoning":[9],"about":[10],"uncertainty":[11],"using":[12],"probability":[13],"theory.":[14],"They":[15],"are":[16],"a":[17,44,74],"probabilistic":[18],"extension":[19],"of":[20,27,30,46,92,104,109],"propositional":[21,31],"logic":[22,51,71,87,96,114,123],"and,":[23],"hence,":[24],"inherit":[25],"some":[26],"the":[28,35,90,102,110],"limitations":[29],"logic,":[32],"such":[33],"as":[34,120,122],"difficulties":[36],"to":[37,53,59],"represent":[38,60],"objects":[39,61],"relations.":[41],"We":[42,83],"introduce":[43],"generalization":[45],"networks,":[48],"called":[49],"programs,":[52],"overcome":[54],"these":[55],"limitations.":[56],"In":[57],"order":[58],"relations":[63],"it":[64],"combines":[65],"with":[68],"definite":[69,94],"clause":[70,95],"by":[72],"establishing":[73],"one-to-one":[75],"mapping":[76],"between":[77],"ground":[78],"atoms":[79],"random":[81],"variables.":[82],"show":[84],"that":[85],"programs":[88,115],"combine":[89],"advantages":[91],"both":[93,117,130],"networks.":[99],"This":[100],"includes":[101],"separation":[103],"quantitative":[105],"qualitative":[107],"aspects":[108],"model.":[111],"Furthermore,":[112],"generalize":[116],"well":[121],"programs.":[124],"So,":[125],"many":[126],"ideas":[127],"developed":[128],"in":[129],"areas":[131],"carry":[132],"over.":[133]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}