{"id":"https://openalex.org/W2782568496","doi":"https://doi.org/10.1109/bigdata.2017.8258495","title":"Event clustering &amp; event series characterization on expected frequency","display_name":"Event clustering &amp; event series characterization on expected frequency","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2782568496","doi":"https://doi.org/10.1109/bigdata.2017.8258495","mag":"2782568496"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8258495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2004.02089","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034296562","display_name":"Conrad M Albrecht","orcid":"https://orcid.org/0009-0009-2422-7289"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210106712","display_name":"Alliance for Safe Kids","ror":"https://ror.org/01922pt58","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210106712"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Conrad M. Albrecht","raw_affiliation_strings":["Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A","institution_ids":["https://openalex.org/I1341412227","https://openalex.org/I4210106712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004915957","display_name":"Marcus Freitag","orcid":"https://orcid.org/0009-0009-0356-7057"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210106712","display_name":"Alliance for Safe Kids","ror":"https://ror.org/01922pt58","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210106712"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Marcus Freitag","raw_affiliation_strings":["Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A","institution_ids":["https://openalex.org/I1341412227","https://openalex.org/I4210106712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082686352","display_name":"Theodore G. van Kessel","orcid":null},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210106712","display_name":"Alliance for Safe Kids","ror":"https://ror.org/01922pt58","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210106712"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Theodore G. van Kessel","raw_affiliation_strings":["Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A","institution_ids":["https://openalex.org/I1341412227","https://openalex.org/I4210106712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084117570","display_name":"Siyuan Lu","orcid":"https://orcid.org/0000-0002-8639-3081"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210106712","display_name":"Alliance for Safe Kids","ror":"https://ror.org/01922pt58","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210106712"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Siyuan Lu","raw_affiliation_strings":["Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A","institution_ids":["https://openalex.org/I1341412227","https://openalex.org/I4210106712"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048701479","display_name":"Hendrik F. Hamann","orcid":"https://orcid.org/0000-0001-9049-1330"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210106712","display_name":"Alliance for Safe Kids","ror":"https://ror.org/01922pt58","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210106712"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hendrik F. Hamann","raw_affiliation_strings":["Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Physical Analytics, IBM Research, Yorktown Heights, NY, U.S.A","institution_ids":["https://openalex.org/I1341412227","https://openalex.org/I4210106712"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19585096,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":null,"first_page":"4536","last_page":"4541"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9965000152587891,"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":0.9965000152587891,"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":0.9932000041007996,"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/T11986","display_name":"Scientific Computing and Data Management","score":0.9890999794006348,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6909170150756836},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6675395369529724},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6427222490310669},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6048887968063354},{"id":"https://openalex.org/keywords/characterization","display_name":"Characterization (materials science)","score":0.4561268091201782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2772371172904968},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.0917101800441742},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07639029622077942}],"concepts":[{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6909170150756836},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6675395369529724},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6427222490310669},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6048887968063354},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.4561268091201782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2772371172904968},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0917101800441742},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07639029622077942},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/bigdata.2017.8258495","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258495","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2004.02089","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.02089","pdf_url":"https://arxiv.org/pdf/2004.02089","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2004.02089","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2004.02089","pdf_url":"https://arxiv.org/pdf/2004.02089","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1481125063","https://openalex.org/W1577231857","https://openalex.org/W1660133578","https://openalex.org/W1673310716","https://openalex.org/W1991040406","https://openalex.org/W2001619934","https://openalex.org/W2049633694","https://openalex.org/W2068947423","https://openalex.org/W2101234009","https://openalex.org/W2146292423","https://openalex.org/W2150593711","https://openalex.org/W2202100984","https://openalex.org/W2282564794","https://openalex.org/W2335584831","https://openalex.org/W2351425503","https://openalex.org/W2472333518","https://openalex.org/W2583417742","https://openalex.org/W2626975733","https://openalex.org/W2779951908","https://openalex.org/W6637052001","https://openalex.org/W6637131181","https://openalex.org/W6675354045"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W3107994849","https://openalex.org/W4247143848","https://openalex.org/W2009883749","https://openalex.org/W2735573198","https://openalex.org/W2390279801","https://openalex.org/W29442446","https://openalex.org/W2358668433","https://openalex.org/W4396701345"],"abstract_inverted_index":{"We":[0],"present":[1],"an":[2,18,28,37,95],"efficient":[3],"clustering":[4],"algorithm":[5],"applicable":[6],"to":[7,63,72,80,89],"one-dimensional":[8],"data":[9,70],"such":[10],"as":[11],"e.g.":[12,64,90],"a":[13,82],"series":[14,39,83],"of":[15,31,40,68,84,94,97],"times-tamps.":[16],"Given":[17],"expected":[19],"frequency":[20],"\u0394T":[21,88],"<sup":[22],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[23,44,49,54],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">-1</sup>":[24],",":[25,46],"we":[26,77],"introduce":[27],"O(N)-efficient":[29],"method":[30,60],"characterizing":[32],"N":[33],"events":[34,85],"represented":[35],"by":[36,86],"ordered":[38],"timestamps":[41],"t":[42,47,52],"<sub":[43,48,53],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sub>":[45],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sub>":[50],",...,":[51],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">N</sub>":[55],".":[56],"In":[57],"practice,":[58],"the":[59,92],"proves":[61],"useful":[62],"identify":[65],"time":[66],"intervals":[67],"missing":[69],"or":[71],"locate":[73],"isolated":[74],"events.":[75],"Moreover,":[76],"define":[78],"measures":[79],"quantify":[81],"varying":[87],"determine":[91],"quality":[93],"Internet":[96],"Things":[98],"service.":[99]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2018-01-26T00:00:00"}