{"id":"https://openalex.org/W2075644155","doi":"https://doi.org/10.1145/2245276.2245308","title":"Hidden markov model-based time series prediction using motifs for detecting inter-time-serial correlations","display_name":"Hidden markov model-based time series prediction using motifs for detecting inter-time-serial correlations","publication_year":2012,"publication_date":"2012-03-26","ids":{"openalex":"https://openalex.org/W2075644155","doi":"https://doi.org/10.1145/2245276.2245308","mag":"2075644155"},"language":"en","primary_location":{"id":"doi:10.1145/2245276.2245308","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2245276.2245308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th Annual ACM Symposium on Applied Computing","raw_type":"proceedings-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/A5031910306","display_name":"Tim Schl\u00fcter","orcid":null},"institutions":[{"id":"https://openalex.org/I44260953","display_name":"Heinrich Heine University D\u00fcsseldorf","ror":"https://ror.org/024z2rq82","country_code":"DE","type":"education","lineage":["https://openalex.org/I44260953"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Tim Schl\u00fcter","raw_affiliation_strings":["Heinrich Heine University, D\u00fcsseldorf (Germany)"],"affiliations":[{"raw_affiliation_string":"Heinrich Heine University, D\u00fcsseldorf (Germany)","institution_ids":["https://openalex.org/I44260953"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037038868","display_name":"Stefan Conrad","orcid":"https://orcid.org/0000-0003-2788-3854"},"institutions":[{"id":"https://openalex.org/I44260953","display_name":"Heinrich Heine University D\u00fcsseldorf","ror":"https://ror.org/024z2rq82","country_code":"DE","type":"education","lineage":["https://openalex.org/I44260953"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Conrad","raw_affiliation_strings":["Heinrich Heine University, D\u00fcsseldorf (Germany)"],"affiliations":[{"raw_affiliation_string":"Heinrich Heine University, D\u00fcsseldorf (Germany)","institution_ids":["https://openalex.org/I44260953"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5031910306"],"corresponding_institution_ids":["https://openalex.org/I44260953"],"apc_list":null,"apc_paid":null,"fwci":1.4691,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.85510414,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"158","last_page":"164"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"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":0.9997000098228455,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9797999858856201,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9613999724388123,"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":0.7077405452728271},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6569811701774597},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.611402153968811},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6041767597198486},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5647568106651306},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5460425019264221},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5244415402412415},{"id":"https://openalex.org/keywords/autocorrelation","display_name":"Autocorrelation","score":0.5124102234840393},{"id":"https://openalex.org/keywords/motif","display_name":"Motif (music)","score":0.44518160820007324},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39749273657798767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37348368763923645},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.266920268535614},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18646380305290222},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16968849301338196}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7077405452728271},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6569811701774597},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.611402153968811},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6041767597198486},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5647568106651306},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5460425019264221},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5244415402412415},{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.5124102234840393},{"id":"https://openalex.org/C32276052","wikidata":"https://www.wikidata.org/wiki/Q908349","display_name":"Motif (music)","level":2,"score":0.44518160820007324},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39749273657798767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37348368763923645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.266920268535614},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18646380305290222},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16968849301338196},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2245276.2245308","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2245276.2245308","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th Annual ACM Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1208489","https://openalex.org/W63520301","https://openalex.org/W69342273","https://openalex.org/W152645600","https://openalex.org/W1490239928","https://openalex.org/W1518144873","https://openalex.org/W1534304300","https://openalex.org/W1544274373","https://openalex.org/W1589170661","https://openalex.org/W1647671624","https://openalex.org/W1662642097","https://openalex.org/W1797971474","https://openalex.org/W1966406756","https://openalex.org/W1967657882","https://openalex.org/W1972677429","https://openalex.org/W1989037929","https://openalex.org/W1992400504","https://openalex.org/W1998871699","https://openalex.org/W2019927194","https://openalex.org/W2060444451","https://openalex.org/W2073308541","https://openalex.org/W2088222765","https://openalex.org/W2091921805","https://openalex.org/W2095484357","https://openalex.org/W2095518456","https://openalex.org/W2098759488","https://openalex.org/W2105594594","https://openalex.org/W2106123304","https://openalex.org/W2111322461","https://openalex.org/W2124192284","https://openalex.org/W2125838338","https://openalex.org/W2128160875","https://openalex.org/W2131286109","https://openalex.org/W2133990480","https://openalex.org/W2141514928","https://openalex.org/W2141899961","https://openalex.org/W2142384583","https://openalex.org/W2144994235","https://openalex.org/W2159123127","https://openalex.org/W2164274563","https://openalex.org/W2166559705","https://openalex.org/W2168486353","https://openalex.org/W2169533279","https://openalex.org/W2238135223","https://openalex.org/W4235234743","https://openalex.org/W4285719527","https://openalex.org/W6672321678"],"related_works":["https://openalex.org/W3170299350","https://openalex.org/W2368410102","https://openalex.org/W2605676258","https://openalex.org/W2368037387","https://openalex.org/W2053269318","https://openalex.org/W2364370872","https://openalex.org/W190186656","https://openalex.org/W2902352756","https://openalex.org/W747394405","https://openalex.org/W2377079823"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3],"approach":[4],"for":[5,42],"time":[6,22,35,51,63],"series":[7,23,36,52],"prediction":[8,44,84],"using":[9],"a":[10,25],"Hidden":[11],"Markov":[12],"Model,":[13],"which":[14,38],"bases":[15],"on":[16,53,88],"inter-time-serial":[17,79],"correlations.":[18],"These":[19],"correlations":[20],"between":[21],"of":[24,45,49,55,70,74,92],"given":[26],"database":[27],"are":[28,86],"automatically":[29],"discovered":[30],"by":[31],"hierarchically":[32],"clustering":[33],"motif-based":[34,76],"representations,":[37],"can":[39],"be":[40],"used":[41],"the":[43,46,59,68,71,75,78,83],"future":[47],"development":[48],"one":[50,60],"base":[54],"known":[56],"values":[57],"from":[58],"and":[61,67,82,96],"correlated":[62],"series.":[64],"The":[65],"functionality":[66],"influence":[69],"different":[72],"parameters":[73],"representation,":[77],"correlation":[80],"discovery":[81],"capability":[85],"evaluated":[87],"two":[89],"large":[90],"databases":[91],"river":[93],"level":[94],"measurements":[95],"stock":[97],"data.":[98]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
