{"id":"https://openalex.org/W7134178656","doi":"https://doi.org/10.1109/bigdata66926.2025.11402055","title":"Automatic Lifestate Identification for High-Dimensional Time Series Data","display_name":"Automatic Lifestate Identification for High-Dimensional Time Series Data","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W7134178656","doi":"https://doi.org/10.1109/bigdata66926.2025.11402055"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata66926.2025.11402055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata66926.2025.11402055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://nottingham-repository.worktribe.com/preview/65538496/Lifestate%20short%20paper.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009639598","display_name":"Samuel S. Smith","orcid":"https://orcid.org/0000-0003-0991-8224"},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Samuel Smith","raw_affiliation_strings":["University of Nottingham,N/LAB,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nottingham,N/LAB,United Kingdom","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Gavin Smith","orcid":null},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gavin Smith","raw_affiliation_strings":["University of Nottingham,N/LAB,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nottingham,N/LAB,United Kingdom","institution_ids":["https://openalex.org/I142263535"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5128366159","display_name":"John Harvey","orcid":null},"institutions":[{"id":"https://openalex.org/I142263535","display_name":"University of Nottingham","ror":"https://ror.org/01ee9ar58","country_code":"GB","type":"education","lineage":["https://openalex.org/I142263535"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"John Harvey","raw_affiliation_strings":["University of Nottingham,N/LAB,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Nottingham,N/LAB,United Kingdom","institution_ids":["https://openalex.org/I142263535"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142263535"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"118"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.6245999932289124,"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":0.6245999932289124,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.03240000084042549,"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/T13248","display_name":"Healthcare Technology and Patient Monitoring","score":0.016200000420212746,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5392000079154968},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4625000059604645},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4551999866962433},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3605000078678131},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.2915000021457672}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5928999781608582},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5392000079154968},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48989999294281006},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4551999866962433},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3605000078678131},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33320000767707825},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2915000021457672},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2800999879837036},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25519999861717224},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25049999356269836}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata66926.2025.11402055","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata66926.2025.11402055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},{"id":"pmh:oai:nottingham-repository.worktribe.com:60456508","is_oa":true,"landing_page_url":"https://nottingham-repository.worktribe.com/60456508/1/Lifestate%20short%20paper","pdf_url":"https://nottingham-repository.worktribe.com/preview/65538496/Lifestate%20short%20paper.pdf","source":{"id":"https://openalex.org/S4306402483","display_name":"Repository@Nottingham (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Presentation / Conference Contribution"}],"best_oa_location":{"id":"pmh:oai:nottingham-repository.worktribe.com:60456508","is_oa":true,"landing_page_url":"https://nottingham-repository.worktribe.com/60456508/1/Lifestate%20short%20paper","pdf_url":"https://nottingham-repository.worktribe.com/preview/65538496/Lifestate%20short%20paper.pdf","source":{"id":"https://openalex.org/S4306402483","display_name":"Repository@Nottingham (University of Nottingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I142263535","host_organization_name":"University of Nottingham","host_organization_lineage":["https://openalex.org/I142263535"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Presentation / Conference Contribution"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7134178656.pdf","grobid_xml":"https://content.openalex.org/works/W7134178656.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W5435836","https://openalex.org/W1680622244","https://openalex.org/W1992222322","https://openalex.org/W2011760672","https://openalex.org/W2015397797","https://openalex.org/W2018416842","https://openalex.org/W2049704739","https://openalex.org/W2077760583","https://openalex.org/W2085039702","https://openalex.org/W2098277968","https://openalex.org/W2107633943","https://openalex.org/W2109240172","https://openalex.org/W2124192284","https://openalex.org/W2165533158","https://openalex.org/W2227557434","https://openalex.org/W2430148303","https://openalex.org/W2563493802","https://openalex.org/W2591589908","https://openalex.org/W2772177579","https://openalex.org/W2892035503","https://openalex.org/W3025787433","https://openalex.org/W3123545922","https://openalex.org/W3217746002","https://openalex.org/W4212812991"],"related_works":[],"abstract_inverted_index":{"Time":[0],"series":[1],"summarisation":[2],"methods":[3,163],"that":[4,200],"account":[5],"for":[6,14,31],"temporal":[7,52],"structure":[8],"in":[9,16,69,88,150],"high-dimensional":[10,45],"data":[11,155],"are":[12],"important":[13],"analysis":[15],"a":[17,40,109,165],"wide":[18],"variety":[19],"of":[20,83,98,112,123,131,167,177,182],"domains,":[21],"yet":[22],"current":[23],"statistical":[24],"and":[25,50,107,126,180],"machine-learning":[26],"tools":[27],"offer":[28],"limited":[29],"support":[30],"this":[32,151],"task.":[33],"We":[34],"introduce":[35],"ALI":[36,101,160,196],"(Automatic":[37],"Lifestate":[38],"Identification),":[39],"parameter-free":[41],"algorithm":[42,106],"that,":[43],"across":[44,55],"time":[46,110,133,188],"series,":[47],"automatically":[48],"identifies":[49],"clusters":[51],"patterns":[53,97],"shared":[54],"entities":[56],"(e.g.":[57],"customers),":[58],"effectively":[59],"capturing":[60],"latent":[61,124,183],"states":[62,125,184],"without":[63,214],"requiring":[64],"manual":[65,215],"tuning.":[66,216],"For":[67],"example,":[68],"retail":[70,194],"settings,":[71],"these":[72],"'latent":[73],"states'":[74],"represent":[75],"distinct,":[76],"persistent":[77],"behavioural":[78],"modes,":[79],"such":[80],"as":[81],"periods":[82],"high-value":[84],"customer":[85],"engagement,":[86],"shifts":[87],"purchasing":[89],"habits":[90],"due":[91],"to":[92,191,207],"life":[93],"events,":[94],"or":[95],"stable":[96],"product":[99],"consumption.":[100],"utilises":[102],"an":[103],"Expectation":[104],"Maximisation":[105],"achieves":[108],"complexity":[111],"O(h":[113],"n":[114,127],"log(n))":[115],"per":[116],"iteration,":[117],"where":[118],"h":[119],"represents":[120],"the":[121,128,146,172],"number":[122,166,181],"total":[129],"length":[130],"concatenated":[132],"series.":[134,189],"Empirical":[135],"results":[136],"show":[137],"fast":[138],"convergence.":[139],"While":[140],"no":[141],"previous":[142],"work":[143],"directly":[144],"addresses":[145],"specific":[147],"problem":[148],"motivated":[149],"work,":[152],"on":[153,186],"synthetic":[154],"with":[156,202],"known":[157,203],"ground":[158],"truth,":[159],"outperforms":[161],"existing":[162],"at":[164],"comparable":[168],"subtasks,":[169],"including":[170],"identifying":[171],"generating":[173],"(k,h)":[174],"pairs":[175],"(number":[176],"segments":[178],"k,":[179],"h)":[185],"single":[187],"Applied":[190],"large":[192],"scale":[193],"transactions,":[195],"recovers":[197],"interpretable":[198],"lifestates":[199],"align":[201],"events":[204],"(e.g.,":[205],"transition":[206],"parenthood),":[208],"yielding":[209],"compact,":[210],"practitioner":[211],"friendly":[212],"summaries":[213]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-09T00:00:00"}
