{"id":"https://openalex.org/W2809503262","doi":"https://doi.org/10.1145/3219819.3219968","title":"SPARC","display_name":"SPARC","publication_year":2018,"publication_date":"2018-07-19","ids":{"openalex":"https://openalex.org/W2809503262","doi":"https://doi.org/10.1145/3219819.3219968","mag":"2809503262"},"language":"en","primary_location":{"id":"doi:10.1145/3219819.3219968","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3219819.3219968","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3219819.3219968","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","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/10.1145/3219819.3219968","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022696348","display_name":"Dawei Zhou","orcid":"https://orcid.org/0000-0002-7065-2990"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dawei Zhou","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073158087","display_name":"Jingrui He","orcid":"https://orcid.org/0000-0002-6429-6272"},"institutions":[{"id":"https://openalex.org/I55732556","display_name":"Arizona State University","ror":"https://ror.org/03efmqc40","country_code":"US","type":"education","lineage":["https://openalex.org/I55732556"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingrui He","raw_affiliation_strings":["Arizona State University, Tempe, AZ, USA"],"affiliations":[{"raw_affiliation_string":"Arizona State University, Tempe, AZ, USA","institution_ids":["https://openalex.org/I55732556"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082599714","display_name":"Hongxia Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxia Yang","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100380588","display_name":"Wei Fan","orcid":"https://orcid.org/0009-0008-1900-7081"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Fan","raw_affiliation_strings":["Tencent Medical AI Lab, Palo Alto, CA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent Medical AI Lab, Palo Alto, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022696348"],"corresponding_institution_ids":["https://openalex.org/I55732556"],"apc_list":null,"apc_paid":null,"fwci":7.2773,"has_fulltext":true,"cited_by_count":64,"citation_normalized_percentile":{"value":0.97634063,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2807","last_page":"2816"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9930999875068665,"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"}},"topics":[{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9930999875068665,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9904999732971191,"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/T10028","display_name":"Topic Modeling","score":0.9836000204086304,"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":0.7050936222076416},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6013962626457214},{"id":"https://openalex.org/keywords/characterization","display_name":"Characterization (materials science)","score":0.5557184815406799},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5374700427055359},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5314300060272217},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5218690633773804},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4909506142139435},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46105968952178955},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37666207551956177},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.34143948554992676},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.34120792150497437},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09984388947486877}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7050936222076416},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6013962626457214},{"id":"https://openalex.org/C2780841128","wikidata":"https://www.wikidata.org/wiki/Q5073781","display_name":"Characterization (materials science)","level":2,"score":0.5557184815406799},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5374700427055359},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5314300060272217},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5218690633773804},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4909506142139435},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46105968952178955},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37666207551956177},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.34143948554992676},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.34120792150497437},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09984388947486877},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C171250308","wikidata":"https://www.wikidata.org/wiki/Q11468","display_name":"Nanotechnology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3219819.3219968","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3219819.3219968","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3219819.3219968","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3219819.3219968","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3219819.3219968","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3219819.3219968","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8100000023841858,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G2022463623","display_name":null,"funder_award_id":"1813464","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2622782994","display_name":"II-NEW: GEARS - An Infrastructure for Energy-Efficient Big Data Research on Heterogeneous and Dynamic Data","funder_award_id":"1629888","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4180941946","display_name":null,"funder_award_id":"CNS-1629888","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4654689037","display_name":null,"funder_award_id":"FA8750-17-C-0153","funder_id":"https://openalex.org/F4320337531","funder_display_name":"Defense Sciences Office, DARPA"},{"id":"https://openalex.org/G4713059963","display_name":null,"funder_award_id":"FA8750","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G5921281487","display_name":null,"funder_award_id":"number","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6608962765","display_name":null,"funder_award_id":"IIS-1552654","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6612472031","display_name":null,"funder_award_id":"2017-ST-061-QA0001","funder_id":"https://openalex.org/F4320306110","funder_display_name":"U.S. Department of Homeland Security"},{"id":"https://openalex.org/G6797398481","display_name":null,"funder_award_id":"CNS-1629888, IIS-1552654","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G79769166","display_name":null,"funder_award_id":"FA8750-17-C-0153","funder_id":"https://openalex.org/F4320332180","funder_display_name":"Defense Advanced Research Projects Agency"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8845068539","display_name":"CAREER: III: Modeling the Heterogeneity of Heterogeneity: Algorithms, Theories and Applications","funder_award_id":"1552654","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"},{"id":"https://openalex.org/F4320306110","display_name":"U.S. Department of Homeland Security","ror":"https://ror.org/00jyr0d86"},{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"},{"id":"https://openalex.org/F4320332467","display_name":"U.S. Air Force","ror":"https://ror.org/006gmme17"},{"id":"https://openalex.org/F4320337531","display_name":"Defense Sciences Office, DARPA","ror":"https://ror.org/0447fe631"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2809503262.pdf","grobid_xml":"https://content.openalex.org/works/W2809503262.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W580709845","https://openalex.org/W1888005072","https://openalex.org/W1910619957","https://openalex.org/W1968154520","https://openalex.org/W1992003426","https://openalex.org/W2001141328","https://openalex.org/W2048679005","https://openalex.org/W2053186076","https://openalex.org/W2109283550","https://openalex.org/W2118978333","https://openalex.org/W2122777361","https://openalex.org/W2132984949","https://openalex.org/W2134969428","https://openalex.org/W2135493362","https://openalex.org/W2137130182","https://openalex.org/W2140189568","https://openalex.org/W2142261479","https://openalex.org/W2142971723","https://openalex.org/W2144415203","https://openalex.org/W2148143831","https://openalex.org/W2154851992","https://openalex.org/W2156718197","https://openalex.org/W2165140157","https://openalex.org/W2166493072","https://openalex.org/W2187089797","https://openalex.org/W2241652765","https://openalex.org/W2256388387","https://openalex.org/W2294494937","https://openalex.org/W2296073425","https://openalex.org/W2440599146","https://openalex.org/W2524741398","https://openalex.org/W2577283662","https://openalex.org/W2584524738","https://openalex.org/W2621438471","https://openalex.org/W2623187518","https://openalex.org/W2740306440","https://openalex.org/W2743013071","https://openalex.org/W2744353700","https://openalex.org/W2755088640","https://openalex.org/W2763694500","https://openalex.org/W2791255512","https://openalex.org/W2808138083","https://openalex.org/W2950133940","https://openalex.org/W2962756421","https://openalex.org/W2963312446","https://openalex.org/W3103254545","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W4246354968","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2329500892","https://openalex.org/W3107994849","https://openalex.org/W28991112","https://openalex.org/W2370726991","https://openalex.org/W2081900870","https://openalex.org/W4247143848","https://openalex.org/W2009883749","https://openalex.org/W2735573198","https://openalex.org/W2369710579","https://openalex.org/W2932872266"],"abstract_inverted_index":{"In":[0],"the":[1,9,65,80,84,88,93,96,100,120,127,132,137],"era":[2],"of":[3,14,75,83,95,99],"big":[4],"data,":[5],"it":[6],"is":[7],"often":[8],"rare":[10,52,66,76,85,113,121,139],"categories":[11,67,86],"that":[12,119],"are":[13,123],"great":[15],"interest":[16],"in":[17,26,34,41,47,131],"many":[18],"high-impact":[19],"applications,":[20],"ranging":[21],"from":[22,37,87,126],"financial":[23],"fraud":[24],"detection":[25,33,40,46],"online":[27],"transaction":[28],"networks":[29,43],"to":[30,44,62],"emerging":[31],"trend":[32],"social":[35],"networks,":[36],"network":[38],"intrusion":[39],"computer":[42],"fault":[45],"manufacturing.":[48],"As":[49],"a":[50,56,103,111],"result,":[51],"category":[53,77,114,140],"characterization":[54],"becomes":[55],"fundamental":[57],"learning":[58],"task,":[59],"which":[60,135],"aims":[61],"accurately":[63],"characterize":[64],"given":[68],"limited":[69],"label":[70],"information.":[71],"The":[72],"unique":[73],"challenge":[74],"characterization,":[78],"i.e.,":[79],"non-separability":[81],"nature":[82],"majority":[89,128],"classes,":[90],"together":[91],"with":[92],"availability":[94],"multi-modal":[97],"representation":[98,117],"examples,":[101],"poses":[102],"new":[104],"research":[105],"question:":[106],"how":[107],"can":[108],"we":[109],"learn":[110],"salient":[112],"oriented":[115],"embedding":[116,133],"such":[118],"examples":[122,130],"well":[124],"separated":[125],"class":[129],"space,":[134],"facilitates":[136],"follow-up":[138],"characterization?":[141]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2018-06-29T00:00:00"}