{"id":"https://openalex.org/W1550211101","doi":"https://doi.org/10.1007/978-3-642-19170-1_10","title":"Personalisation in Service-Oriented Systems Using Markov Chain Model and Bayesian Inference","display_name":"Personalisation in Service-Oriented Systems Using Markov Chain Model and Bayesian Inference","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W1550211101","doi":"https://doi.org/10.1007/978-3-642-19170-1_10","mag":"1550211101"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-642-19170-1_10","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-19170-1_10","pdf_url":null,"source":{"id":"https://openalex.org/S4210175514","display_name":"IFIP International Federation for Information Processing/IFIP","issn_l":"1571-5736","issn":["1571-5736","1861-2288"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IFIP Advances in Information and Communication Technology","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://inria.hal.science/hal-01566550","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004385039","display_name":"Jakub M. Tomczak","orcid":"https://orcid.org/0000-0001-8634-694X"},"institutions":[{"id":"https://openalex.org/I4210087266","display_name":"Institute of Computer Science","ror":"https://ror.org/003fvp964","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210087266","https://openalex.org/I99542240"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Jakub M. Tomczak","raw_affiliation_strings":["Faculty of Computer Science and Management, Institute of Computer Science, Wybrze\u017ce Wyspia\u0144skiego 27, 50-370, Wroc\u0142aw, Poland"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science and Management, Institute of Computer Science, Wybrze\u017ce Wyspia\u0144skiego 27, 50-370, Wroc\u0142aw, Poland","institution_ids":["https://openalex.org/I4210087266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083502688","display_name":"Jerzy \u015awi\u0105tek","orcid":"https://orcid.org/0000-0002-4986-8092"},"institutions":[{"id":"https://openalex.org/I4210087266","display_name":"Institute of Computer Science","ror":"https://ror.org/003fvp964","country_code":"PL","type":"facility","lineage":["https://openalex.org/I4210087266","https://openalex.org/I99542240"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jerzy \u015awi\u0105tek","raw_affiliation_strings":["Faculty of Computer Science and Management, Institute of Computer Science, Wybrze\u017ce Wyspia\u0144skiego 27, 50-370, Wroc\u0142aw, Poland"],"affiliations":[{"raw_affiliation_string":"Faculty of Computer Science and Management, Institute of Computer Science, Wybrze\u017ce Wyspia\u0144skiego 27, 50-370, Wroc\u0142aw, Poland","institution_ids":["https://openalex.org/I4210087266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004385039"],"corresponding_institution_ids":["https://openalex.org/I4210087266"],"apc_list":null,"apc_paid":null,"fwci":3.6765,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.92828302,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"91","last_page":"98"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9674999713897705,"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/T12384","display_name":"Customer churn and segmentation","score":0.9465000033378601,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.7354761362075806},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.696286141872406},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6539543867111206},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6255236864089966},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5970768928527832},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5513170957565308},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.5484217405319214},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5012884140014648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4682140350341797},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.4486173391342163},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.442770391702652},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.42975562810897827},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3702171742916107},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.3427885174751282},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16944265365600586},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13873982429504395},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09021937847137451}],"concepts":[{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.7354761362075806},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.696286141872406},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6539543867111206},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6255236864089966},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5970768928527832},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5513170957565308},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.5484217405319214},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5012884140014648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4682140350341797},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.4486173391342163},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.442770391702652},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.42975562810897827},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3702171742916107},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.3427885174751282},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16944265365600586},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13873982429504395},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09021937847137451}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/978-3-642-19170-1_10","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-19170-1_10","pdf_url":null,"source":{"id":"https://openalex.org/S4210175514","display_name":"IFIP International Federation for Information Processing/IFIP","issn_l":"1571-5736","issn":["1571-5736","1861-2288"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IFIP Advances in Information and Communication Technology","raw_type":"book-chapter"},{"id":"pmh:oai:HAL:hal-01566550v1","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-01566550","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2nd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2011, Costa de Caparica, Portugal. pp.91-98, ⟨10.1007/978-3-642-19170-1_10⟩","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-01566550v1","is_oa":true,"landing_page_url":"https://inria.hal.science/hal-01566550","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2nd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2011, Costa de Caparica, Portugal. pp.91-98, ⟨10.1007/978-3-642-19170-1_10⟩","raw_type":"Conference papers"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1545151502","https://openalex.org/W1556655003","https://openalex.org/W1566318844","https://openalex.org/W1585419630","https://openalex.org/W1614686989","https://openalex.org/W2037079123","https://openalex.org/W2057552436","https://openalex.org/W2061812145","https://openalex.org/W2124756613","https://openalex.org/W2138444337","https://openalex.org/W2139338182","https://openalex.org/W2140004670","https://openalex.org/W2503370639","https://openalex.org/W2561675875","https://openalex.org/W2571084211","https://openalex.org/W4211084959"],"related_works":["https://openalex.org/W2151689585","https://openalex.org/W2380816257","https://openalex.org/W2109940557","https://openalex.org/W3087071515","https://openalex.org/W2466832359","https://openalex.org/W4283726152","https://openalex.org/W1582019636","https://openalex.org/W3093571331","https://openalex.org/W1499005795","https://openalex.org/W1525770572"],"abstract_inverted_index":{"In":[0],"the":[1,19,31,36,43,56,84],"paper":[2],"a":[3,25],"personalization":[4],"method":[5],"using":[6],"Markov":[7,44],"model":[8],"and":[9,118],"Bayesian":[10],"inference":[11],"is":[12,16,28,53,67,89,94,106],"presented.":[13],"The":[14,47,91,104],"idea":[15],"based":[17,108],"on":[18,96,109],"hypothesis":[20],"that":[21],"user\u2019s":[22,37],"choice":[23],"of":[24,65,99,116],"new":[26],"decision":[27],"influenced":[29],"by":[30,42,69],"last":[32],"made":[33,68],"decision.":[34],"Thus,":[35],"behaviour":[38,52],"could":[39],"be":[40],"described":[41],"chain":[45],"model.":[46],"extracted":[48],"knowledge":[49],"about":[50],"users\u2019":[51,121],"maintained":[54],"in":[55],"transition":[57],"matrice":[58],"as":[59],"probability":[60],"distribution":[61],"functions.":[62],"An":[63],"estimation":[64],"probabilities":[66],"applying":[70],"incremental":[71],"learning":[72],"algorithm":[73],"which":[74],"allows":[75],"to":[76,102],"cope":[77],"with":[78],"evolving":[79,120],"environments":[80],"(e.g.":[81],"preferences).":[82],"At":[83],"end":[85],"an":[86,97],"empirical":[87],"study":[88],"given.":[90],"proposed":[92],"approach":[93],"presented":[95],"example":[98],"students":[100],"enrolling":[101],"courses.":[103],"dataset":[105],"partially":[107],"real-life":[110],"data":[111],"taken":[112],"from":[113],"Wroc\u0142aw":[114],"University":[115],"Technology":[117],"includes":[119],"behaviour.":[122]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":3}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}