{"id":"https://openalex.org/W1995239016","doi":"https://doi.org/10.1109/grc.2005.1547275","title":"Analysis of numeric data streams at different granularities","display_name":"Analysis of numeric data streams at different granularities","publication_year":2005,"publication_date":"2005-01-01","ids":{"openalex":"https://openalex.org/W1995239016","doi":"https://doi.org/10.1109/grc.2005.1547275","mag":"1995239016"},"language":"en","primary_location":{"id":"doi:10.1109/grc.2005.1547275","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2005.1547275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2005 IEEE International Conference on Granular 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/A5015222262","display_name":"Mehmet Sayal","orcid":null},"institutions":[{"id":"https://openalex.org/I1324840837","display_name":"Hewlett-Packard (United States)","ror":"https://ror.org/059rn9488","country_code":"US","type":"company","lineage":["https://openalex.org/I1324840837"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M. Sayal","raw_affiliation_strings":["Hewlett Packard Laboratories, Palo Alto, CA, USA","Hewlett\u2013Packard Laboratories, Palo Alto, CA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Laboratories, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I1324840837"]},{"raw_affiliation_string":"Hewlett\u2013Packard Laboratories, Palo Alto, CA, USA#TAB#","institution_ids":["https://openalex.org/I1324840837"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044295245","display_name":"M.-C. Shan","orcid":"https://orcid.org/0000-0002-2455-4812"},"institutions":[{"id":"https://openalex.org/I1324840837","display_name":"Hewlett-Packard (United States)","ror":"https://ror.org/059rn9488","country_code":"US","type":"company","lineage":["https://openalex.org/I1324840837"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"M.-C. Shan","raw_affiliation_strings":["Hewlett Packard Laboratories, Palo Alto, CA, USA","Hewlett\u2013Packard Laboratories, Palo Alto, CA, USA#TAB#"],"affiliations":[{"raw_affiliation_string":"Hewlett Packard Laboratories, Palo Alto, CA, USA","institution_ids":["https://openalex.org/I1324840837"]},{"raw_affiliation_string":"Hewlett\u2013Packard Laboratories, Palo Alto, CA, USA#TAB#","institution_ids":["https://openalex.org/I1324840837"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015222262"],"corresponding_institution_ids":["https://openalex.org/I1324840837"],"apc_list":null,"apc_paid":null,"fwci":0.9538,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.74530126,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"237","last_page":"242 Vol. 1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9829000234603882,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.963100016117096,"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/data-stream-mining","display_name":"Data stream mining","score":0.8152643442153931},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.7458480596542358},{"id":"https://openalex.org/keywords/streams","display_name":"STREAMS","score":0.736840009689331},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7366542816162109},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6933042407035828},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6455756425857544},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6038026809692383},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5766462683677673},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.41081100702285767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.18455472588539124},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1346403956413269}],"concepts":[{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.8152643442153931},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.7458480596542358},{"id":"https://openalex.org/C42090638","wikidata":"https://www.wikidata.org/wiki/Q4048907","display_name":"STREAMS","level":2,"score":0.736840009689331},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7366542816162109},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6933042407035828},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6455756425857544},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6038026809692383},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5766462683677673},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.41081100702285767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.18455472588539124},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1346403956413269},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/grc.2005.1547275","is_oa":false,"landing_page_url":"https://doi.org/10.1109/grc.2005.1547275","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2005 IEEE International Conference on Granular 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":21,"referenced_works":["https://openalex.org/W1499049447","https://openalex.org/W1514224985","https://openalex.org/W1562291184","https://openalex.org/W1581831035","https://openalex.org/W1587157435","https://openalex.org/W1826290430","https://openalex.org/W1864972570","https://openalex.org/W2002328435","https://openalex.org/W2053062040","https://openalex.org/W2086086639","https://openalex.org/W2128061541","https://openalex.org/W2143702666","https://openalex.org/W2537653680","https://openalex.org/W2904372083","https://openalex.org/W4212848460","https://openalex.org/W4249116379","https://openalex.org/W6629760146","https://openalex.org/W6633551152","https://openalex.org/W6634887016","https://openalex.org/W6635259333","https://openalex.org/W6639107604"],"related_works":["https://openalex.org/W4293083682","https://openalex.org/W4389449520","https://openalex.org/W2061507057","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W4361801939","https://openalex.org/W2360131081","https://openalex.org/W2985941356"],"abstract_inverted_index":{"A":[0],"novel":[1],"method":[2,21,26,111],"for":[3,102],"analyzing":[4],"time-series":[5,14,36,59,76,86],"data":[6,15,37,60,77,87,99],"and":[7,30,56,95,115],"extracting":[8],"time-correlations":[9],"(time-dependent":[10],"relationships)":[11],"among":[12,34,44],"multiple":[13,35],"streams":[16,78],"is":[17,22,112],"described.":[18],"The":[19],"proposed":[20],"the":[23,42,52,67,70,80,109,124],"first":[24],"online":[25],"that":[27,108],"can":[28,91],"detect":[29],"report":[31],"time-dependent":[32],"relationships":[33,43],"streams.":[38,61,88],"Time-correlations":[39],"tell":[40],"us":[41],"numeric":[45],"variables":[46],"whose":[47],"values":[48,71,81],"are":[49],"recorded":[50],"over":[51],"course":[53],"of":[54,72,75,85,126],"time":[55,120],"transmitted":[57],"using":[58],"Each":[62],"time-correlation":[63],"rule":[64],"explains":[65],"how":[66],"changes":[68],"in":[69,82],"one":[73],"set":[74,84],"influence":[79],"another":[83],"Those":[89],"rules":[90],"be":[92],"stored":[93],"digitally":[94],"fed":[96],"into":[97],"various":[98],"analysis":[100],"tools":[101],"further":[103],"analysis.":[104],"Performance":[105],"experiments":[106],"showed":[107],"described":[110],"95%":[113],"accurate,":[114],"has":[116],"a":[117],"linear":[118],"running":[119],"with":[121],"respect":[122],"to":[123],"amount":[125],"input":[127],"data.":[128]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
