{"id":"https://openalex.org/W2988384045","doi":"https://doi.org/10.1145/3357384.3358162","title":"Deep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity","display_name":"Deep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity","publication_year":2019,"publication_date":"2019-11-03","ids":{"openalex":"https://openalex.org/W2988384045","doi":"https://doi.org/10.1145/3357384.3358162","mag":"2988384045"},"language":"en","primary_location":{"id":"doi:10.1145/3357384.3358162","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3357384.3358162","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3357384.3358162","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th 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/10.1145/3357384.3358162","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","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, South Bend, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame, South Bend, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","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":false,"raw_author_name":"Xian Wu","raw_affiliation_strings":["University of Notre Dame, South Bend, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame, South Bend, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101905948","display_name":"Xuchao Zhang","orcid":"https://orcid.org/0000-0001-5344-456X"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xuchao Zhang","raw_affiliation_strings":["Virginia Tech, Blacksburg, VA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051213779","display_name":"Suwen Lin","orcid":null},"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":"Suwen Lin","raw_affiliation_strings":["University of Notre Dame, South Bend, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame, South Bend, 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, South Bend, IN, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Notre Dame, South Bend, IN, USA","institution_ids":["https://openalex.org/I107639228"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5021,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.83675208,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2141","last_page":"2144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9965000152587891,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9746999740600586,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"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/computer-science","display_name":"Computer science","score":0.727745532989502},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6727735996246338},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.6678053140640259},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5970325469970703},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5773929357528687},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.565079391002655},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5638688802719116},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5527936220169067},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5439886450767517},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.5305419564247131},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5192068219184875},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5009348392486572},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.46886757016181946},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4453759491443634},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41199174523353577},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09346997737884521}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.727745532989502},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6727735996246338},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.6678053140640259},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5970325469970703},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5773929357528687},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.565079391002655},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5638688802719116},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5527936220169067},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5439886450767517},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.5305419564247131},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5192068219184875},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5009348392486572},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.46886757016181946},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4453759491443634},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41199174523353577},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09346997737884521},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3357384.3358162","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3357384.3358162","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3357384.3358162","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3357384.3358162","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3357384.3358162","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3357384.3358162","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1162675597","display_name":null,"funder_award_id":"-1629914","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"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/G4029481580","display_name":null,"funder_award_id":"1447795","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4360170584","display_name":"II-New: Infrastructure for Supporting Biomedical Application Algorithms, Runtime Development and Resource Management","funder_award_id":"1629914","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7420284228","display_name":null,"funder_award_id":"CNS-1629914","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2988384045.pdf","grobid_xml":"https://content.openalex.org/works/W2988384045.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1975257359","https://openalex.org/W1993220166","https://openalex.org/W2035104901","https://openalex.org/W2037537012","https://openalex.org/W2104933073","https://openalex.org/W2141350700","https://openalex.org/W2237307454","https://openalex.org/W2288074780","https://openalex.org/W2306394264","https://openalex.org/W2403172465","https://openalex.org/W2432717477","https://openalex.org/W2434388418","https://openalex.org/W2551393996","https://openalex.org/W2601450892","https://openalex.org/W2754051771","https://openalex.org/W2800788706","https://openalex.org/W2897825916","https://openalex.org/W3010296268"],"related_works":["https://openalex.org/W2783354812","https://openalex.org/W4384112194","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W4308259661","https://openalex.org/W4390813131","https://openalex.org/W2349383066","https://openalex.org/W4328132048","https://openalex.org/W1969901537","https://openalex.org/W2119768059"],"abstract_inverted_index":{"With":[0],"the":[1,17,55,69,104,140],"increase":[2],"of":[3,14,20,24,57,106],"temporal":[4],"data":[5,62,113,141],"availability,":[6],"time":[7,51,108,147],"series":[8,52,109,148],"classification":[9,53],"has":[10,46],"drawn":[11],"a":[12,89,98,123,133],"lot":[13],"attention":[15],"in":[16,26],"literature":[18],"because":[19],"its":[21],"wide":[22],"spectrum":[23],"applications":[25],"diverse":[27],"domains":[28],"(e.g.,":[29],"healthcare,":[30],"bioinformatics":[31],"and":[32,64,78,144,154],"finance),":[33],"ranging":[34],"from":[35],"human":[36],"activity":[37],"recognition":[38],"to":[39,49,102,127,158],"financial":[40],"pattern":[41],"identification.":[42],"While":[43],"significant":[44,153],"progress":[45],"been":[47],"made":[48],"solve":[50],"problem,":[54],"success":[56],"such":[58],"methods":[59],"relies":[60],"on":[61],"sufficiency,":[63],"may":[65],"not":[66],"well":[67],"capture":[68,103],"quality":[70],"embeddings":[71],"when":[72],"training":[73],"triple":[74],"instances":[75],"are":[76],"scarce":[77],"highly":[79],"imbalance":[80,142],"across":[81],"classes.":[82],"To":[83],"address":[84],"these":[85],"challenges,":[86],"we":[87,117],"propose":[88],"prototype":[90],"embedding":[91,100],"framework-Deep":[92],"Prototypical":[93],"Networks":[94],"(DPN),":[95],"which":[96,138],"leverages":[97],"main":[99],"space":[101],"discrepancies":[105],"difference":[107],"classes":[110],"for":[111],"alleviating":[112],"scarcity.":[114],"In":[115],"addition,":[116],"further":[118],"augment":[119],"DPN":[120],"framework":[121],"with":[122,132],"relationship-dependent":[124],"masking":[125],"module":[126],"automatically":[128],"fuse":[129],"relevant":[130],"information":[131],"distance":[134],"metric":[135],"learning":[136],"process,":[137],"addresses":[139],"issue":[143],"performs":[145],"robust":[146],"classification.":[149],"Experimental":[150],"results":[151],"show":[152],"consistent":[155],"improvements":[156],"compared":[157],"state-of-the-art":[159],"techniques.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}