{"id":"https://openalex.org/W2257386194","doi":"https://doi.org/10.1145/2833312.2849556","title":"Incremental time series algorithms for IoT analytics","display_name":"Incremental time series algorithms for IoT analytics","publication_year":2016,"publication_date":"2016-01-04","ids":{"openalex":"https://openalex.org/W2257386194","doi":"https://doi.org/10.1145/2833312.2849556","mag":"2257386194"},"language":"en","primary_location":{"id":"doi:10.1145/2833312.2849556","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2833312.2849556","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Distributed Computing and Networking","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/A5048505159","display_name":"Debnath Mukherjee","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Debnath Mukherjee","raw_affiliation_strings":["Tata Consultancy Services, New Town, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Tata Consultancy Services, New Town, Kolkata, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036105393","display_name":"Suman Datta","orcid":"https://orcid.org/0000-0001-6044-5173"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Suman Datta","raw_affiliation_strings":["Tata Consultancy Services, New Town, Kolkata, India"],"affiliations":[{"raw_affiliation_string":"Tata Consultancy Services, New Town, Kolkata, India","institution_ids":["https://openalex.org/I55215948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5048505159"],"corresponding_institution_ids":["https://openalex.org/I55215948"],"apc_list":null,"apc_paid":null,"fwci":0.5179,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.61621457,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9991999864578247,"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":0.9991999864578247,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9976000189781189,"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/T11106","display_name":"Data Management and Algorithms","score":0.9810000061988831,"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/computer-science","display_name":"Computer science","score":0.8233146667480469},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.607871413230896},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5694559216499329},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5636742115020752},{"id":"https://openalex.org/keywords/memory-footprint","display_name":"Memory footprint","score":0.5518355369567871},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.5366273522377014},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5163080096244812},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5133072733879089},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.48624387383461},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4408474862575531},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4233362674713135},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2118147313594818},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07884091138839722}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8233146667480469},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.607871413230896},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5694559216499329},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5636742115020752},{"id":"https://openalex.org/C74912251","wikidata":"https://www.wikidata.org/wiki/Q6815727","display_name":"Memory footprint","level":2,"score":0.5518355369567871},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.5366273522377014},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5163080096244812},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5133072733879089},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.48624387383461},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4408474862575531},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4233362674713135},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2118147313594818},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07884091138839722},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"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:10.1145/2833312.2849556","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2833312.2849556","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th International Conference on Distributed Computing and Networking","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2100473839","https://openalex.org/W2141245797","https://openalex.org/W2173213060","https://openalex.org/W2223115626","https://openalex.org/W2514415618","https://openalex.org/W2947626232"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W4394895745","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2910064364","https://openalex.org/W4200136508","https://openalex.org/W2349019353"],"abstract_inverted_index":{"The":[0],"Internet":[1],"of":[2,20,26,34,40,65,74],"Things":[3],"(IoT)":[4],"is":[5,29,37],"emerging":[6],"as":[7],"an":[8,93,97],"important":[9],"application":[10],"area":[11],"for":[12,82,96],"time":[13,21,31,99],"series":[14,32,100],"statistical":[15],"analysis":[16,33,101],"and":[17,85,112],"data":[18,28,36],"mining":[19],"series.":[22],"As":[23],"the":[24,45,55,114],"volume":[25],"sensor":[27,35],"high,":[30],"a":[38,107],"problem":[39],"processing":[41],"large":[42,60,63],"datasets.":[43],"Moreover,":[44],"IoT":[46],"platforms":[47],"have":[48],"to":[49],"simultaneously":[50],"process":[51],"multiple":[52],"jobs":[53],"on":[54],"same":[56],"infrastructure.":[57],"Processing":[58],"such":[59],"datasets":[61],"requires":[62],"amount":[64],"memory.":[66],"To":[67],"alleviate":[68],"this":[69,89,121],"problem,":[70],"we":[71,91],"propose":[72],"use":[73],"incremental":[75,94,122],"algorithms.":[76],"Incremental":[77],"algorithms":[78],"can":[79],"be":[80],"used":[81],"both":[83],"batch":[84],"streaming":[86],"applications.":[87],"In":[88],"paper,":[90],"show":[92,113],"algorithm":[95,102,111],"example":[98],"viz.":[103],"autoregression.":[104],"We":[105],"describe":[106],"memory":[108,115],"efficient":[109],"autoregression":[110],"footprint":[116],"reduction":[117],"achieved":[118],"by":[119],"using":[120],"algorithm.":[123]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
