{"id":"https://openalex.org/W2897825916","doi":"https://doi.org/10.1145/3269206.3271794","title":"RESTFul","display_name":"RESTFul","publication_year":2018,"publication_date":"2018-10-17","ids":{"openalex":"https://openalex.org/W2897825916","doi":"https://doi.org/10.1145/3269206.3271794","mag":"2897825916"},"language":"en","primary_location":{"id":"doi:10.1145/3269206.3271794","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3269206.3271794","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3269206.3271794","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3269206.3271794","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100352416","display_name":"Xian Wu","orcid":"https://orcid.org/0000-0003-0840-5857"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xian Wu","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101424783","display_name":"Baoxu Shi","orcid":"https://orcid.org/0000-0001-7026-5811"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Baoxu Shi","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052284218","display_name":"Yuxiao Dong","orcid":"https://orcid.org/0000-0002-6092-2002"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxiao Dong","raw_affiliation_strings":["Microsoft Research, Redmond, WA, USA"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102025800","display_name":"Chao Huang","orcid":"https://orcid.org/0000-0003-3800-5766"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chao Huang","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076011510","display_name":"Louis Faust","orcid":"https://orcid.org/0000-0002-9741-7894"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Louis Faust","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068157871","display_name":"Nitesh V. Chawla","orcid":"https://orcid.org/0000-0003-3932-5956"},"institutions":[{"id":"https://openalex.org/I107639228","display_name":"University of Notre Dame","ror":"https://ror.org/00mkhxb43","country_code":"US","type":"education","lineage":["https://openalex.org/I107639228"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nitesh V. Chawla","raw_affiliation_strings":["University of Notre Dame, Notre Dame, IN, USA"],"affiliations":[{"raw_affiliation_string":"University of Notre Dame, Notre Dame, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100352416"],"corresponding_institution_ids":["https://openalex.org/I107639228"],"apc_list":null,"apc_paid":null,"fwci":4.3112,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.95350501,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1073","last_page":"1082"},"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/T12761","display_name":"Data Stream Mining Techniques","score":0.998199999332428,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9941999912261963,"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":0.7718181610107422},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6317192316055298},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.5867316722869873},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.582192063331604},{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.5602075457572937},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5337050557136536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49790453910827637},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.49293971061706543},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4673096835613251},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.456870973110199},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44763901829719543}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7718181610107422},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6317192316055298},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.5867316722869873},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.582192063331604},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.5602075457572937},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5337050557136536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49790453910827637},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.49293971061706543},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4673096835613251},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.456870973110199},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44763901829719543},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3269206.3271794","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3269206.3271794","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3269206.3271794","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3269206.3271794","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3269206.3271794","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3269206.3271794","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3142689400","display_name":null,"funder_award_id":"IIS-1447795","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3488221432","display_name":null,"funder_award_id":"IIS-1447795 and CNS-1622914","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G360105532","display_name":null,"funder_award_id":"CNS-1622914","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4029481580","display_name":null,"funder_award_id":"1447795","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5259331294","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"},{"id":"https://openalex.org/G7561134949","display_name":null,"funder_award_id":"W911NF-09-2-0053","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G948678646","display_name":null,"funder_award_id":"W911NF-09-2-0053","funder_id":"https://openalex.org/F4320338295","funder_display_name":"Army Research Laboratory"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2897825916.pdf","grobid_xml":"https://content.openalex.org/works/W2897825916.grobid-xml"},"referenced_works_count":45,"referenced_works":["https://openalex.org/W1603920809","https://openalex.org/W1832693441","https://openalex.org/W1924770834","https://openalex.org/W1971402834","https://openalex.org/W1986078433","https://openalex.org/W1989037929","https://openalex.org/W1991001067","https://openalex.org/W2035104901","https://openalex.org/W2055079831","https://openalex.org/W2061039971","https://openalex.org/W2065460148","https://openalex.org/W2086634749","https://openalex.org/W2093546394","https://openalex.org/W2095705004","https://openalex.org/W2096706838","https://openalex.org/W2108447256","https://openalex.org/W2117143037","https://openalex.org/W2120615054","https://openalex.org/W2127838378","https://openalex.org/W2153635508","https://openalex.org/W2158382689","https://openalex.org/W2163302320","https://openalex.org/W2172073485","https://openalex.org/W2181523240","https://openalex.org/W2276747974","https://openalex.org/W2373739222","https://openalex.org/W2400964651","https://openalex.org/W2537810077","https://openalex.org/W2583674722","https://openalex.org/W2585021848","https://openalex.org/W2604764001","https://openalex.org/W2605350416","https://openalex.org/W2613328025","https://openalex.org/W2624190409","https://openalex.org/W2690721124","https://openalex.org/W2742940593","https://openalex.org/W2744939564","https://openalex.org/W2746272363","https://openalex.org/W2767434259","https://openalex.org/W2777938864","https://openalex.org/W2802679249","https://openalex.org/W2949117887","https://openalex.org/W2950178297","https://openalex.org/W3099136959","https://openalex.org/W3199947862"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W2103419012","https://openalex.org/W2988126442","https://openalex.org/W4386799044","https://openalex.org/W2773208253","https://openalex.org/W1974414866","https://openalex.org/W2560646951","https://openalex.org/W4297454206"],"abstract_inverted_index":{"Leveraging":[0],"historical":[1],"behavioral":[2,51,79,139,169],"data":[3,82,142],"(e.g.,":[4,37],"sales":[5,22],"volume":[6],"and":[7,90,167],"email":[8],"communication)":[9],"for":[10,17,78,137],"future":[11,145],"prediction":[12,162],"is":[13,127,130],"of":[14,45,86,132],"fundamental":[15],"importance":[16],"practical":[18],"domains":[19],"ranging":[20],"from":[21],"to":[23,111,143],"temporal":[24,47,59,114,135],"link":[25],"prediction.":[26],"Current":[27],"forecasting":[28,76,96],"approaches":[29],"often":[30],"use":[31],"only":[32],"a":[33,92,108,123],"single":[34],"time":[35,52,80,88,94,140,146,160,170],"resolution":[36],"daily":[38],"or":[39],"weekly),":[40],"which":[41,129],"truncates":[42],"the":[43,75,84,113,120,153,158],"range":[44],"observable":[46],"patterns.":[48],"However,":[49],"real-world":[50],"series":[53,81,95,100,141,161,171],"typically":[54],"exhibit":[55],"patterns":[56,115,136],"across":[57],"multi-dimensional":[58],"patterns,":[60],"yielding":[61],"dependencies":[62],"at":[63,116],"each":[64,117],"level.":[65],"To":[66],"fully":[67],"exploit":[68],"these":[69],"underlying":[70],"dynamics,":[71],"this":[72],"paper":[73],"studies":[74],"problem":[77],"with":[83],"consideration":[85],"multiple":[87],"resolutions":[89],"proposes":[91],"multi-resolution":[93],"framework,":[97],"RESolution-aware":[98],"Time":[99],"Forecasting":[101],"(RESTFul).":[102],"In":[103,119],"particular,":[104],"we":[105],"first":[106],"develop":[107],"recurrent":[109],"framework":[110,126],"encode":[112],"resolution.":[118],"fusion":[121,125],"process,":[122],"convolutional":[124],"proposed,":[128],"capable":[131],"learning":[133],"conclusive":[134],"modeling":[138],"predict":[144],"steps.":[147],"Our":[148],"extensive":[149],"experiments":[150],"demonstrate":[151],"that":[152],"RESTFul":[154],"model":[155],"significantly":[156],"outperforms":[157],"state-of-the-art":[159],"techniques":[163],"on":[164],"both":[165],"numerical":[166],"categorical":[168],"data.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2018-10-26T00:00:00"}
