{"id":"https://openalex.org/W2783988861","doi":"https://doi.org/10.1109/iske.2017.8258812","title":"A model for the detection of underlying trends in temporal data","display_name":"A model for the detection of underlying trends in temporal data","publication_year":2017,"publication_date":"2017-11-01","ids":{"openalex":"https://openalex.org/W2783988861","doi":"https://doi.org/10.1109/iske.2017.8258812","mag":"2783988861"},"language":"en","primary_location":{"id":"doi:10.1109/iske.2017.8258812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2017.8258812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","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/A5027177184","display_name":"Ity Kaul","orcid":null},"institutions":[{"id":"https://openalex.org/I113979032","display_name":"Twitter (United States)","ror":"https://ror.org/04wt43v05","country_code":"US","type":"company","lineage":["https://openalex.org/I113979032"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ity Kaul","raw_affiliation_strings":["University of NSW, Sydney Twitter, Inc., California"],"affiliations":[{"raw_affiliation_string":"University of NSW, Sydney Twitter, Inc., California","institution_ids":["https://openalex.org/I113979032"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027881741","display_name":"\u00c9ric Martin","orcid":"https://orcid.org/0000-0001-8832-7478"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eric Martin","raw_affiliation_strings":["University of NSW, Sydney"],"affiliations":[{"raw_affiliation_string":"University of NSW, Sydney","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049492016","display_name":"Vishal Puri","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vishal Puri","raw_affiliation_strings":["Inferess, Inc., California"],"affiliations":[{"raw_affiliation_string":"Inferess, Inc., California","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5027177184"],"corresponding_institution_ids":["https://openalex.org/I113979032"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20320155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"10 3","issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9994000196456909,"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":0.9994000196456909,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9732999801635742,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9681000113487244,"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/computer-science","display_name":"Computer science","score":0.7787414789199829},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.6017407178878784},{"id":"https://openalex.org/keywords/interval","display_name":"Interval (graph theory)","score":0.5931398868560791},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.551051914691925},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5481545925140381},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5339862704277039},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5137122869491577},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4949612021446228},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.48560088872909546},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.4607381224632263},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4081316292285919},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4039378762245178},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10835707187652588}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7787414789199829},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.6017407178878784},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.5931398868560791},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.551051914691925},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5481545925140381},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5339862704277039},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5137122869491577},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4949612021446228},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.48560088872909546},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.4607381224632263},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4081316292285919},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4039378762245178},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10835707187652588},{"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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iske.2017.8258812","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iske.2017.8258812","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.4099999964237213,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W42584966","https://openalex.org/W1483365869","https://openalex.org/W1560368109","https://openalex.org/W1894414046","https://openalex.org/W1969022715","https://openalex.org/W1981258337","https://openalex.org/W1986225012","https://openalex.org/W1990139510","https://openalex.org/W1994496890","https://openalex.org/W1995609782","https://openalex.org/W1995875735","https://openalex.org/W2027475942","https://openalex.org/W2043735243","https://openalex.org/W2060975088","https://openalex.org/W2082951961","https://openalex.org/W2088563154","https://openalex.org/W2089700840","https://openalex.org/W2091442045","https://openalex.org/W2105009836","https://openalex.org/W2118992504","https://openalex.org/W2125099364","https://openalex.org/W2132549764","https://openalex.org/W2141281200","https://openalex.org/W2154892776","https://openalex.org/W2158591439","https://openalex.org/W2161832826","https://openalex.org/W2163336863","https://openalex.org/W2408196097","https://openalex.org/W2467711758","https://openalex.org/W2607051590","https://openalex.org/W2797532987","https://openalex.org/W3045904630","https://openalex.org/W3124979809","https://openalex.org/W4238015707","https://openalex.org/W4238717354","https://openalex.org/W4239854775","https://openalex.org/W4302437350","https://openalex.org/W6601729303","https://openalex.org/W6661268684","https://openalex.org/W6714332745","https://openalex.org/W6719571795"],"related_works":["https://openalex.org/W42295635","https://openalex.org/W1973996291","https://openalex.org/W2330575325","https://openalex.org/W2140798747","https://openalex.org/W2163803519","https://openalex.org/W2497592525","https://openalex.org/W2948169060","https://openalex.org/W3096145648","https://openalex.org/W3197510923","https://openalex.org/W2370579019"],"abstract_inverted_index":{"Trend":[0],"detection":[1,161],"in":[2],"financial":[3,61],"temporal":[4],"data":[5,35],"is":[6,54,79,91],"a":[7,25,45,48,88,109,115,126,130,138,153,159,168],"significant":[8,127],"problem,":[9],"with":[10,16],"far-reaching":[11],"applications,":[12],"that":[13,37,53,90,111,170],"presents":[14],"researchers":[15],"many":[17],"challenges.":[18],"Existing":[19],"techniques":[20],"require":[21],"users":[22,113],"to":[23,57,75,83,86,95,107,187],"choose":[24],"given":[26],"interval,":[27],"and":[28,93,136,150,183],"then":[29],"provide":[30],"an":[31,123],"approximation":[32,124],"of":[33,47,50,98,132,140,167],"the":[34,96,119,133,141,165,172,179,193],"on":[36,101,121,178],"interval;":[38],"they":[39,190],"always":[40],"produce":[41],"some":[42,58],"approximation,":[43],"namely,":[44],"member":[46],"class":[49],"candidate":[51],"functions":[52],"\"best\"":[55],"according":[56],"criteria.":[59],"Moreover,":[60],"analysis":[62,97],"can":[63,196],"be":[64,84,197],"performed":[65],"from":[66,72,192,199],"different":[67,70],"perspectives,":[68],"at":[69],"levels,":[71],"short":[73],"term":[74],"long":[76],"term;":[77],"it":[78],"therefore":[80],"very":[81],"desirable":[82],"able":[85],"indicate":[87],"scale":[89,116,134],"suitable":[92],"adapted":[94],"interest.":[99],"Based":[100],"these":[102],"considerations,":[103],"our":[104],"objective":[105],"was":[106],"design":[108],"method":[110,144],"lets":[112],"input":[114],"factor,":[117,135],"determines":[118],"intervals":[120],"which":[122],"captures":[125],"trend":[128],"as":[129],"function":[131],"proposes":[137],"qualification":[139],"trend.":[142],"The":[143],"we":[145,176,181],"use":[146,184],"combines":[147],"various":[148],"machine-learning":[149],"statistical":[151],"techniques,":[152],"key":[154],"role":[155],"being":[156],"played":[157],"by":[158],"change-point":[160],"method.":[162,174],"We":[163],"describe":[164],"architecture":[166],"system":[169],"implements":[171],"proposed":[173],"Finally,":[175],"report":[177],"experiments":[180],"ran":[182],"their":[185],"results":[186,194],"stress":[188],"how":[189],"differ":[191],"than":[195],"obtained":[198],"alternative":[200],"approaches.":[201]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
