{"id":"https://openalex.org/W3035022413","doi":"https://doi.org/10.24963/ijcai.2020/334","title":"Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data","display_name":"Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3035022413","doi":"https://doi.org/10.24963/ijcai.2020/334","mag":"3035022413"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/334","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/334","pdf_url":"https://www.ijcai.org/proceedings/2020/0334.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0334.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088294917","display_name":"Masahiro Kohjima","orcid":null},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masahiro Kohjima","raw_affiliation_strings":["NTT Corporation","NTT Service Evolution Laboratories, NTT Corporation, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Service Evolution Laboratories, NTT Corporation, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056228425","display_name":"Takeshi Kurashima","orcid":"https://orcid.org/0000-0002-1641-4799"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takeshi Kurashima","raw_affiliation_strings":["NTT Corporation","NTT Service Evolution Laboratories, NTT Corporation, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Service Evolution Laboratories, NTT Corporation, Japan","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101576701","display_name":"Hiroyuki Toda","orcid":"https://orcid.org/0000-0003-4883-527X"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroyuki Toda","raw_affiliation_strings":["NTT Corporation","NTT Service Evolution Laboratories, NTT Corporation, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTT Corporation","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Service Evolution Laboratories, NTT Corporation, Japan","institution_ids":["https://openalex.org/I2251713219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2251713219"],"apc_list":null,"apc_paid":null,"fwci":0.1643,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.30257802,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2412","last_page":"2419"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.98580002784729,"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":0.9822999835014343,"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":0.7106484770774841},{"id":"https://openalex.org/keywords/transition","display_name":"Transition (genetics)","score":0.650161862373352},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.5428692102432251},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.5415113568305969},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5355159640312195},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5246092081069946},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.510917603969574},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4700820744037628},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4230573773384094},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.41849568486213684},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41756972670555115},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3613394498825073},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2584080696105957},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1418720781803131},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12567594647407532},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08786216378211975}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7106484770774841},{"id":"https://openalex.org/C194232998","wikidata":"https://www.wikidata.org/wiki/Q1606712","display_name":"Transition (genetics)","level":3,"score":0.650161862373352},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.5428692102432251},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5415113568305969},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5355159640312195},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5246092081069946},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.510917603969574},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4700820744037628},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4230573773384094},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.41849568486213684},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41756972670555115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3613394498825073},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2584080696105957},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1418720781803131},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12567594647407532},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08786216378211975},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2020/334","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/334","pdf_url":"https://www.ijcai.org/proceedings/2020/0334.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/334","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/334","pdf_url":"https://www.ijcai.org/proceedings/2020/0334.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.699999988079071,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3035022413.pdf","grobid_xml":"https://content.openalex.org/works/W3035022413.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1556598185","https://openalex.org/W1967687583","https://openalex.org/W1976099204","https://openalex.org/W1989540460","https://openalex.org/W2036995503","https://openalex.org/W2049633694","https://openalex.org/W2051434435","https://openalex.org/W2069429561","https://openalex.org/W2077806964","https://openalex.org/W2080972498","https://openalex.org/W2083970694","https://openalex.org/W2099196192","https://openalex.org/W2102524069","https://openalex.org/W2106317109","https://openalex.org/W2127498532","https://openalex.org/W2128221272","https://openalex.org/W2149414429","https://openalex.org/W2154602821","https://openalex.org/W2329077652","https://openalex.org/W2550626811","https://openalex.org/W2615785394","https://openalex.org/W2808008404","https://openalex.org/W2885549115","https://openalex.org/W3122680493","https://openalex.org/W4230277433","https://openalex.org/W4237780050","https://openalex.org/W4248548277","https://openalex.org/W4296927530","https://openalex.org/W4298838381","https://openalex.org/W4301048281"],"related_works":["https://openalex.org/W4380150146","https://openalex.org/W3024870410","https://openalex.org/W2410652950","https://openalex.org/W2053269318","https://openalex.org/W2364370872","https://openalex.org/W2379651310","https://openalex.org/W2113019827","https://openalex.org/W1541249122","https://openalex.org/W2413828414","https://openalex.org/W2367222340"],"abstract_inverted_index":{"Due":[0],"to":[1,22,89,123],"the":[2,33,91,95,109,112,125,141,144],"difficulty":[3],"of":[4,62,114,128,143],"comprehensive":[5],"data":[6,26,59,65,78,100],"collection,":[7],"created":[8],"by":[9,146],"factors":[10],"such":[11],"as":[12,101],"privacy":[13],"protection":[14],"and":[15,75,97,103,132,150],"sensor":[16],"device":[17],"limitations,":[18],"we":[19,41],"often":[20],"need":[21],"analyze":[23],"incomplete":[24,57],"transition":[25,36,58,64,77,99,106,130],"where":[27,108],"some":[28,82],"information":[29,71],"is":[30,72,93],"missing":[31],"from":[32,56,67,80],"ideal":[34],"(complete)":[35],"data.":[37,152],"In":[38],"this":[39],"paper,":[40],"propose":[42],"a":[43,50,135],"new":[44,136],"method":[45,92],"that":[46,60],"can":[47],"estimate,":[48],"in":[49],"unified":[51],"manner,":[52],"Markov":[53],"chain":[54],"parameters":[55],"consist":[61],"hidden":[63,96],"(data":[66,79],"which":[68,81],"visited":[69],"state":[70,83],"partially":[73],"hidden)":[74],"dropped":[76,98],"visits":[84],"are":[85],"dropped).":[86],"A":[87],"key":[88],"developing":[90],"regarding":[94],"labeled":[102],"unlabeled":[104],"multi-step":[105,129],"data,":[107,131],"labels":[110],"represent":[111],"number":[113],"steps":[115],"required":[116],"for":[117],"each":[118],"transition.":[119],"This":[120],"allows":[121],"us":[122],"describe":[124],"generative":[126],"process":[127],"thus":[133],"develop":[134],"probabilistic":[137],"model.":[138],"We":[139],"confirm":[140],"effectiveness":[142],"proposal":[145],"experiments":[147],"on":[148],"synthetic":[149],"real":[151]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}