{"id":"https://openalex.org/W2003106649","doi":"https://doi.org/10.1145/1871437.1871537","title":"A method for discovering components of human rituals from streams of sensor data","display_name":"A method for discovering components of human rituals from streams of sensor data","publication_year":2010,"publication_date":"2010-10-26","ids":{"openalex":"https://openalex.org/W2003106649","doi":"https://doi.org/10.1145/1871437.1871537","mag":"2003106649"},"language":"en","primary_location":{"id":"doi:10.1145/1871437.1871537","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1871437.1871537","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM international conference on Information and knowledge management","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/A5041802292","display_name":"Athanasios Bamis","orcid":null},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Athanasios Bamis","raw_affiliation_strings":["Yale University, New Haven, CT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101562545","display_name":"Jia Fang","orcid":"https://orcid.org/0000-0001-8241-209X"},"institutions":[{"id":"https://openalex.org/I919571938","display_name":"The University of Texas Health Science Center at Houston","ror":"https://ror.org/03gds6c39","country_code":"US","type":"education","lineage":["https://openalex.org/I919571938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jia Fang","raw_affiliation_strings":["University of Texas Health Science Center at Houston, Houston, TX, USA","University of Texas, Health Science Center at Houston, Houston, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas Health Science Center at Houston, Houston, TX, USA","institution_ids":["https://openalex.org/I919571938"]},{"raw_affiliation_string":"University of Texas, Health Science Center at Houston, Houston, TX, USA","institution_ids":["https://openalex.org/I919571938"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027175650","display_name":"Andreas Savvides","orcid":"https://orcid.org/0000-0002-0759-1275"},"institutions":[{"id":"https://openalex.org/I32971472","display_name":"Yale University","ror":"https://ror.org/03v76x132","country_code":"US","type":"education","lineage":["https://openalex.org/I32971472"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas Savvides","raw_affiliation_strings":["Yale University, New Haven, CT, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yale University, New Haven, CT, USA","institution_ids":["https://openalex.org/I32971472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3545,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.7998094,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"779","last_page":"788"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9987000226974487,"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":0.9987000226974487,"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/T11309","display_name":"Music and Audio Processing","score":0.9986000061035156,"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/T11106","display_name":"Data Management and Algorithms","score":0.9976999759674072,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.8045048713684082},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.7726315259933472},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.754629909992218},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.7054282426834106},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.678674578666687},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6249904632568359},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.6111496686935425},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5272998809814453},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5004806518554688},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4040347635746002},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33689796924591064},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14951571822166443}],"concepts":[{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.8045048713684082},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.7726315259933472},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.754629909992218},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.7054282426834106},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.678674578666687},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6249904632568359},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.6111496686935425},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5272998809814453},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5004806518554688},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4040347635746002},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33689796924591064},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14951571822166443},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1871437.1871537","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1871437.1871537","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM international conference on Information and knowledge management","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.187.5896","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.187.5896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.bamis.gr/papers/bamis_cikm10.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.41999998688697815,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1484413656","https://openalex.org/W1506285740","https://openalex.org/W1590683836","https://openalex.org/W1625346917","https://openalex.org/W1861465509","https://openalex.org/W2018804066","https://openalex.org/W2020534703","https://openalex.org/W2049633694","https://openalex.org/W2066680326","https://openalex.org/W2090667601","https://openalex.org/W2108072252","https://openalex.org/W2115826098","https://openalex.org/W2118887058","https://openalex.org/W2126310301","https://openalex.org/W2144621085","https://openalex.org/W2156026066"],"related_works":["https://openalex.org/W2883256816","https://openalex.org/W2171408034","https://openalex.org/W3003320923","https://openalex.org/W2106140982","https://openalex.org/W2152313554","https://openalex.org/W2064303750","https://openalex.org/W1509300825","https://openalex.org/W3092582874","https://openalex.org/W2338718585","https://openalex.org/W2054620577"],"abstract_inverted_index":{"This":[0,47],"paper":[1,81],"describes":[2],"an":[3,8,13],"algorithm":[4,29],"for":[5],"determining":[6],"if":[7],"event":[9,22],"occurs":[10],"persistently":[11],"within":[12],"interval":[14,17,42],"where":[15],"the":[16,21,28,40,57,73,76,103],"is":[18,23,30,49],"periodic":[19],"but":[20],"not.":[24],"The":[25],"goal":[26],"of":[27,59,66,94,102],"to":[31],"identify":[32],"events":[33,99],"with":[34],"this":[35,80,90],"property":[36],"and":[37,68,75,87],"also":[38],"determine":[39],"minimum":[41],"in":[43,79],"which":[44,98],"they":[45],"occur.":[46],"solution":[48],"geared":[50],"towards":[51],"discovering":[52],"human":[53],"routines":[54,95],"by":[55,96],"considering":[56],"triggering":[58],"simple":[60],"sensors":[61],"over":[62],"a":[63],"diverse":[64],"set":[65],"spatial":[67],"temporal":[69,108],"scales.":[70],"After":[71],"describing":[72],"problem":[74],"proposed":[77],"solution,":[78],"we":[82],"demonstrate":[83],"using":[84],"testbed":[85],"data":[86],"simulations":[88],"that":[89],"approach":[91],"uncovers":[92],"components":[93],"identifying":[97],"are":[100],"parts":[101],"same":[104],"routine":[105],"through":[106],"their":[107],"properties.":[109]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2013,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
