{"id":"https://openalex.org/W2138215503","doi":"https://doi.org/10.1002/(sici)1098-111x(199708)12:8<553::aid-int1>3.0.co;2-j","title":"Mixing exact and importance sampling propagation algorithms in dependence graphs","display_name":"Mixing exact and importance sampling propagation algorithms in dependence graphs","publication_year":1997,"publication_date":"1997-08-01","ids":{"openalex":"https://openalex.org/W2138215503","doi":"https://doi.org/10.1002/(sici)1098-111x(199708)12:8<553::aid-int1>3.0.co;2-j","mag":"2138215503"},"language":"en","primary_location":{"id":"doi:10.1002/(sici)1098-111x(199708)12:8<553::aid-int1>3.0.co;2-j","is_oa":false,"landing_page_url":"https://doi.org/10.1002/(sici)1098-111x(199708)12:8<553::aid-int1>3.0.co;2-j","pdf_url":null,"source":{"id":"https://openalex.org/S57950554","display_name":"International Journal of Intelligent Systems","issn_l":"0884-8173","issn":["0884-8173","1098-111X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Systems","raw_type":"journal-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/A5097966010","display_name":"Luis D. Hern\ufffdndez","orcid":null},"institutions":[{"id":"https://openalex.org/I80180929","display_name":"Universidad de Murcia","ror":"https://ror.org/03p3aeb86","country_code":"ES","type":"education","lineage":["https://openalex.org/I80180929"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Luis D. Hern\ufffdndez","raw_affiliation_strings":["Dpto. de Inform\u00e1tica y Sistemas, Facultad de Inform\u00e1tica, Universidad de Murcia, 30071, Espinardo, Murcia, Spain"],"affiliations":[{"raw_affiliation_string":"Dpto. de Inform\u00e1tica y Sistemas, Facultad de Inform\u00e1tica, Universidad de Murcia, 30071, Espinardo, Murcia, Spain","institution_ids":["https://openalex.org/I80180929"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085932877","display_name":"Seraf\ufffdn Moral","orcid":null},"institutions":[{"id":"https://openalex.org/I173304897","display_name":"Universidad de Granada","ror":"https://ror.org/04njjy449","country_code":"ES","type":"education","lineage":["https://openalex.org/I173304897"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Seraf\ufffdn Moral","raw_affiliation_strings":["Dpto. CC. de la Computacio\u0301n e I.A., E.T.S. de Informa\u0301tica, Avd. de Andaluci\u0301a, 38, Universidad de Granada, 18071 Granada, Spain","Dpto. CC. de la Computaci\u00f3n e I.A., E.T.S. de Inform\u00e1tica, Avd. de Andaluc\u00eda, 38, Universidad de Granada, 18071 Granada, Spain"],"affiliations":[{"raw_affiliation_string":"Dpto. CC. de la Computacio\u0301n e I.A., E.T.S. de Informa\u0301tica, Avd. de Andaluci\u0301a, 38, Universidad de Granada, 18071 Granada, Spain","institution_ids":["https://openalex.org/I173304897"]},{"raw_affiliation_string":"Dpto. CC. de la Computaci\u00f3n e I.A., E.T.S. de Inform\u00e1tica, Avd. de Andaluc\u00eda, 38, Universidad de Granada, 18071 Granada, Spain","institution_ids":["https://openalex.org/I173304897"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5097966010"],"corresponding_institution_ids":["https://openalex.org/I80180929"],"apc_list":{"value":2500,"currency":"USD","value_usd":2500},"apc_paid":null,"fwci":1.1701,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.83753784,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"12","issue":"8","first_page":"553","last_page":"576"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.9990000128746033,"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":0.9990000128746033,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.98089998960495,"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/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.691564679145813},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6736008524894714},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6307806372642517},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6272479891777039},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5993541479110718},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.578127920627594},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.5309270024299622},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.49884033203125},{"id":"https://openalex.org/keywords/rejection-sampling","display_name":"Rejection sampling","score":0.49641257524490356},{"id":"https://openalex.org/keywords/k-d-tree","display_name":"k-d tree","score":0.4184833765029907},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34706413745880127},{"id":"https://openalex.org/keywords/hybrid-monte-carlo","display_name":"Hybrid Monte Carlo","score":0.3229537606239319},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.202880859375},{"id":"https://openalex.org/keywords/tree-traversal","display_name":"Tree traversal","score":0.1830175220966339},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14700376987457275},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.07775697112083435}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.691564679145813},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6736008524894714},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6307806372642517},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6272479891777039},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5993541479110718},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.578127920627594},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.5309270024299622},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.49884033203125},{"id":"https://openalex.org/C187192777","wikidata":"https://www.wikidata.org/wiki/Q381699","display_name":"Rejection sampling","level":5,"score":0.49641257524490356},{"id":"https://openalex.org/C33721204","wikidata":"https://www.wikidata.org/wiki/Q309949","display_name":"k-d tree","level":3,"score":0.4184833765029907},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34706413745880127},{"id":"https://openalex.org/C13153151","wikidata":"https://www.wikidata.org/wiki/Q1639846","display_name":"Hybrid Monte Carlo","level":4,"score":0.3229537606239319},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.202880859375},{"id":"https://openalex.org/C140745168","wikidata":"https://www.wikidata.org/wiki/Q1210082","display_name":"Tree traversal","level":2,"score":0.1830175220966339},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14700376987457275},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.07775697112083435},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/(sici)1098-111x(199708)12:8<553::aid-int1>3.0.co;2-j","is_oa":false,"landing_page_url":"https://doi.org/10.1002/(sici)1098-111x(199708)12:8<553::aid-int1>3.0.co;2-j","pdf_url":null,"source":{"id":"https://openalex.org/S57950554","display_name":"International Journal of Intelligent Systems","issn_l":"0884-8173","issn":["0884-8173","1098-111X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W20626266","https://openalex.org/W111380827","https://openalex.org/W1484324861","https://openalex.org/W1554743847","https://openalex.org/W1561981064","https://openalex.org/W1630331242","https://openalex.org/W1791798111","https://openalex.org/W1919989817","https://openalex.org/W1980452149","https://openalex.org/W1999432334","https://openalex.org/W2015071685","https://openalex.org/W2029834535","https://openalex.org/W2090361527","https://openalex.org/W2093976733","https://openalex.org/W2110293626","https://openalex.org/W2114307208","https://openalex.org/W2137901101","https://openalex.org/W2147632348","https://openalex.org/W2279566492","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W916027","https://openalex.org/W2116791275","https://openalex.org/W105676162","https://openalex.org/W4360849015","https://openalex.org/W2310467276","https://openalex.org/W2592308920","https://openalex.org/W4287979791","https://openalex.org/W2998420136","https://openalex.org/W2949594430","https://openalex.org/W2984753240"],"abstract_inverted_index":{"In":[0],"this":[1,75],"article":[2],"a":[3,20,24,60,81,134],"new":[4],"algorithm":[5,86],"is":[6,17,67,116],"presented":[7],"for":[8,55],"the":[9,29,37,46,56,78,96,104,111,123],"propagation":[10],"of":[11,28,63,89,98,131],"probabilities":[12],"in":[13,80,110],"junction":[14,25,82],"trees.":[15],"It":[16],"based":[18],"on":[19,77,95],"hybrid":[21],"methodology.":[22],"Given":[23],"tree,":[26],"some":[27,88],"nodes":[30],"carry":[31],"out":[32],"an":[33,39],"exact":[34,47],"calculation,":[35],"and":[36,54,87],"other":[38],"approximation":[40],"by":[41],"Monte":[42,57],"Carlo":[43,58],"methods.":[44],"For":[45],"calculation":[48],"we":[49,102],"will":[50],"use":[51],"Shafer/Shenoy":[52],"method":[53],"estimation":[59],"general":[61],"class":[62],"importance":[64,105],"sampling":[65],"algorithms":[66],"used.":[68],"We":[69],"briefly":[70],"study":[71],"how":[72],"to":[73,100],"apply":[74,103],"sampler":[76],"clusters":[79],"tree.":[83,112],"The":[84],"basic":[85],"its":[90],"variations":[91],"are":[92],"presented,":[93],"depending":[94],"family":[97,130],"functions":[99],"which":[101],"sampler:":[106],"potentials":[107],"or/and":[108],"messages":[109],"An":[113],"experimental":[114],"evaluation":[115],"carried":[117],"out,":[118],"comparing":[119],"their":[120],"performance":[121],"with":[122],"well-known":[124],"likelihood":[125],"weighting":[126],"approximated":[127],"algorithm.":[128],"This":[129],"methods":[132],"shows":[133],"very":[135],"promising":[136],"performance.":[137],"\u00a9":[138],"John":[139],"Wiley":[140],"&":[141],"Sons,":[142],"Inc.":[143]},"counts_by_year":[{"year":2018,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
