{"id":"https://openalex.org/W72871559","doi":null,"title":"Toward Markov Logic with Conditional Probabilities.","display_name":"Toward Markov Logic with Conditional Probabilities.","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W72871559","mag":"72871559"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.135.8347","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.8347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://osiris.cs.ru.nl/~arjenh/rc/papers/markovprobconstraintsflairs2008.pdf","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/A5023840585","display_name":"Jens Fisseler","orcid":"https://orcid.org/0000-0003-1551-3565","observed_orcids":["https://orcid.org/0000-0003-1551-3565"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jens Fisseler","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-1551-3565","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5023840585"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3982,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.84819689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"643","last_page":"648"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9731000065803528,"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":0.9731000065803528,"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":0.025200000032782555,"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":0.00019999999494757503,"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/markov-logic-networks","display_name":"Markov logic networks","score":0.996999979019165},{"id":"https://openalex.org/keywords/conditional-probability","display_name":"conditional probability","score":0.8820000290870667},{"id":"https://openalex.org/keywords/probabilistic-relational-models","display_name":"probabilistic relational models","score":0.8130000233650208},{"id":"https://openalex.org/keywords/first-order-logic","display_name":"first-order logic","score":0.5789999961853027},{"id":"https://openalex.org/keywords/probabilistic-knowledge-representation","display_name":"probabilistic knowledge representation","score":0.7599999904632568},{"id":"https://openalex.org/keywords/prior-knowledge","display_name":"prior knowledge","score":0.6420000195503235},{"id":"https://openalex.org/keywords/probabilistic-expert-systems","display_name":"probabilistic expert systems","score":0.8709999918937683}],"concepts":[{"id":"https://openalex.org/C171018156","wikidata":"https://www.wikidata.org/wiki/Q7370306","display_name":"Rotation formalisms in three dimensions","level":2,"score":0.7530240416526794},{"id":"https://openalex.org/C52063229","wikidata":"https://www.wikidata.org/wiki/Q7246845","display_name":"Probabilistic CTL","level":4,"score":0.7512373924255371},{"id":"https://openalex.org/C128828806","wikidata":"https://www.wikidata.org/wiki/Q7246848","display_name":"Probabilistic argumentation","level":3,"score":0.7057169079780579},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6820523738861084},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.6149247884750366},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5967974066734314},{"id":"https://openalex.org/C18998212","wikidata":"https://www.wikidata.org/wiki/Q7246856","display_name":"Probabilistic logic network","level":5,"score":0.5711811184883118},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5650050640106201},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5490588545799255},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.4609767198562622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45920947194099426},{"id":"https://openalex.org/C102993220","wikidata":"https://www.wikidata.org/wiki/Q387196","display_name":"Description logic","level":2,"score":0.35321033000946045},{"id":"https://openalex.org/C3845977","wikidata":"https://www.wikidata.org/wiki/Q4826262","display_name":"Autoepistemic logic","level":4,"score":0.3237617015838623},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3140392601490021},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3036057651042938},{"id":"https://openalex.org/C203659156","wikidata":"https://www.wikidata.org/wiki/Q6934805","display_name":"Multimodal logic","level":3,"score":0.2742796242237091},{"id":"https://openalex.org/C24404364","wikidata":"https://www.wikidata.org/wiki/Q7246846","display_name":"Probabilistic analysis of algorithms","level":3,"score":0.13557350635528564},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.1311587393283844},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.10957786440849304},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.135.8347","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.135.8347","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://osiris.cs.ru.nl/~arjenh/rc/papers/markovprobconstraintsflairs2008.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.664.5336","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.664.5336","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/FLAIRS/2008/FLAIRS08-144.pdf","raw_type":"text"},{"id":"mag:72871559","doi":null,"is_oa":false,"landing_page_url":"https://www.aaai.org/Papers/FLAIRS/2008/FLAIRS08-144.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306421048","display_name":"The Florida AI Research Society","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"The Florida AI Research Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W34871118","https://openalex.org/W1497576442","https://openalex.org/W1504110645","https://openalex.org/W1513861746","https://openalex.org/W1528272070","https://openalex.org/W1585529040","https://openalex.org/W1746680969","https://openalex.org/W1843494895","https://openalex.org/W2001792610","https://openalex.org/W2003373550","https://openalex.org/W2036945895","https://openalex.org/W2052958516","https://openalex.org/W2054358802","https://openalex.org/W2068962858","https://openalex.org/W2097903822","https://openalex.org/W2107272354","https://openalex.org/W2120853830","https://openalex.org/W2126151607","https://openalex.org/W2149612380","https://openalex.org/W2159080219","https://openalex.org/W2540540486","https://openalex.org/W3090721158"],"related_works":["https://openalex.org/W1977970897","https://openalex.org/W7100879931","https://openalex.org/W7098723116","https://openalex.org/W2396789290","https://openalex.org/W1760731167","https://openalex.org/W2117234103","https://openalex.org/W7097008286","https://openalex.org/W2121075864","https://openalex.org/W2597132876","https://openalex.org/W7097081958"],"abstract_inverted_index":{"Combining":[0],"probability":[1,22],"and":[2,23,38,129],"first-order":[3,27,58],"logic":[4,28,35,40,59,63,110],"has":[5],"been":[6],"the":[7,13,49,55,71,87,114,119,132,144],"sub-ject":[8],"of":[9,26,57,70,89,116,121,146],"intensive":[10],"research":[11],"during":[12],"last":[14],"ten":[15],"years.":[16],"The":[17],"most":[18,51],"well-known":[19],"formalisms":[20],"combining":[21],"some":[24],"sub-set":[25],"are":[29],"probabilistic":[30,76,149],"relational":[31],"models":[32],"(PRMs),":[33],"Bayesian":[34],"programs":[36],"(BLPs)":[37],"Markov":[39,62,109],"networks":[41,64],"(MLNs).":[42],"Of":[43],"these":[44],"three":[45],"formalisms,":[46,74],"MLN":[47],"is":[48,65,78],"currently":[50],"actively":[52],"researched.":[53],"While":[54],"subset":[56],"used":[60],"by":[61,80],"more":[66],"expressive":[67],"than":[68],"that":[69],"other":[72],"two":[73],"its":[75],"seman-tics":[77],"given":[79],"weights":[81],"assigned":[82],"to":[83,107],"formulas,":[84],"which":[85,112],"limits":[86],"comprehensibility":[88],"MLNs.":[90],"Based":[91],"on":[92],"a":[93,122],"knowledge":[94,137],"rep-resentation":[95],"formalism":[96],"developed":[97],"for":[98,118,134,143,148],"propositional":[99],"probabilis-tic":[100],"models,":[101],"we":[102],"propose":[103],"an":[104],"alternative":[105],"way":[106,133],"specify":[108],"networks,":[111],"allows":[113],"specification":[115],"probabili-ties":[117],"formulas":[120],"MLN.":[123],"This":[124],"results":[125],"in":[126],"better":[127],"com-prehensibility,":[128],"might":[130],"open":[131],"using":[135],"background":[136],"when":[138],"learning":[139],"MLNs":[140,147],"or":[141],"even":[142],"use":[145],"expert":[150],"systems.":[151]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":4}],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2016-06-24T00:00:00"}