{"id":"https://openalex.org/W2948720235","doi":"https://doi.org/10.1145/3299869.3319862","title":"Event Trend Aggregation Under Rich Event Matching Semantics","display_name":"Event Trend Aggregation Under Rich Event Matching Semantics","publication_year":2019,"publication_date":"2019-06-18","ids":{"openalex":"https://openalex.org/W2948720235","doi":"https://doi.org/10.1145/3299869.3319862","mag":"2948720235"},"language":"en","primary_location":{"id":"doi:10.1145/3299869.3319862","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3299869.3319862","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3299869.3319862","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Conference on Management of Data","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3299869.3319862","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071632366","display_name":"Olga Poppe","orcid":"https://orcid.org/0000-0002-8578-307X"},"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":"Olga Poppe","raw_affiliation_strings":["Microsoft Gray Systems Lab, Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Gray Systems Lab, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004959524","display_name":"Chuan Lei","orcid":"https://orcid.org/0000-0001-6265-9554"},"institutions":[{"id":"https://openalex.org/I4210085935","display_name":"IBM Research - Almaden","ror":"https://ror.org/005w8dd04","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210085935","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chuan Lei","raw_affiliation_strings":["IBM Research - Almaden, San Jose, CA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research - Almaden, San Jose, CA, USA","institution_ids":["https://openalex.org/I4210085935"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008269094","display_name":"Elke A. Rundensteiner","orcid":"https://orcid.org/0000-0001-5375-9254"},"institutions":[{"id":"https://openalex.org/I107077323","display_name":"Worcester Polytechnic Institute","ror":"https://ror.org/05ejpqr48","country_code":"US","type":"education","lineage":["https://openalex.org/I107077323"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Elke A. Rundensteiner","raw_affiliation_strings":["Worcester Polytechnic Institute, Worcester, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute, Worcester, MA, USA","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014301644","display_name":"David Maier","orcid":"https://orcid.org/0000-0003-4790-5619"},"institutions":[{"id":"https://openalex.org/I126345244","display_name":"Portland State University","ror":"https://ror.org/00yn2fy02","country_code":"US","type":"education","lineage":["https://openalex.org/I126345244"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Maier","raw_affiliation_strings":["Portland State University, Portland, OR, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Portland State University, Portland, OR, USA","institution_ids":["https://openalex.org/I126345244"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"555","last_page":"572"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.9994999766349792,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/granularity","display_name":"Granularity","score":0.8539168238639832},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8075953722000122},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.7666311264038086},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.7092024683952332},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.6394768953323364},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6042559146881104},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.48743966221809387},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4318244755268097},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.42486122250556946},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22225603461265564},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.19267591834068298},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1411455273628235},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1060992181301117}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.8539168238639832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8075953722000122},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.7666311264038086},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7092024683952332},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.6394768953323364},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6042559146881104},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48743966221809387},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4318244755268097},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.42486122250556946},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22225603461265564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.19267591834068298},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1411455273628235},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1060992181301117},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3299869.3319862","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3299869.3319862","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3299869.3319862","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Conference on Management of Data","raw_type":"proceedings-article"},{"id":"pmh:oai:pdxscholar.library.pdx.edu:compsci_fac-1237","is_oa":false,"landing_page_url":"https://pdxscholar.library.pdx.edu/compsci_fac/234","pdf_url":null,"source":{"id":"https://openalex.org/S4377196300","display_name":"PDXScholar  (Portland State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126345244","host_organization_name":"Portland State University","host_organization_lineage":["https://openalex.org/I126345244"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computer Science Faculty Publications and Presentations","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3299869.3319862","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3299869.3319862","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3299869.3319862","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 International Conference on Management of Data","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1246219950","display_name":"III:  Small:  Complex Event Analytics","funder_award_id":"1018443","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3612169079","display_name":null,"funder_award_id":"IIS 1018443, IIS 343620, IIS 1560229, CRI 1305258","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4083504884","display_name":null,"funder_award_id":"IIS-1815866","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5436171597","display_name":"III: Small: Scalable Event Trend Analytics For Data Stream Inquiry","funder_award_id":"1815866","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8106998152","display_name":"II-EN:   Compute Infrastructure for Large-Scale Data Analytics","funder_award_id":"1305258","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/W2948720235.pdf","grobid_xml":"https://content.openalex.org/works/W2948720235.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W79504326","https://openalex.org/W1495986321","https://openalex.org/W1550449994","https://openalex.org/W1572028520","https://openalex.org/W1584003909","https://openalex.org/W1990800901","https://openalex.org/W1999968379","https://openalex.org/W2001002317","https://openalex.org/W2009602724","https://openalex.org/W2010173932","https://openalex.org/W2045478235","https://openalex.org/W2052464302","https://openalex.org/W2063598276","https://openalex.org/W2085426673","https://openalex.org/W2096679630","https://openalex.org/W2101717554","https://openalex.org/W2102654168","https://openalex.org/W2103201239","https://openalex.org/W2115482638","https://openalex.org/W2123458705","https://openalex.org/W2126490564","https://openalex.org/W2143792095","https://openalex.org/W2147694185","https://openalex.org/W2149233085","https://openalex.org/W2150346598","https://openalex.org/W2153794097","https://openalex.org/W2153836901","https://openalex.org/W2156026066","https://openalex.org/W2156157921","https://openalex.org/W2156212081","https://openalex.org/W2156488464","https://openalex.org/W2164595803","https://openalex.org/W2165207129","https://openalex.org/W2166597031","https://openalex.org/W2166604013","https://openalex.org/W2613057181","https://openalex.org/W2623567496","https://openalex.org/W2766012695","https://openalex.org/W2790658561","https://openalex.org/W2963895360","https://openalex.org/W2963962416"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W4382701072","https://openalex.org/W2943576608"],"abstract_inverted_index":{"Streaming":[0],"applications":[1],"from":[2,50],"cluster":[3],"monitoring":[4],"to":[5,11,23,126,134,142],"algorithmic":[6],"trading":[7],"deploy":[8],"Kleene":[9],"queries":[10],"detect":[12],"and":[13,53,116,132],"aggregate":[14],"event":[15,18,81],"trends.":[16,27],"Rich":[17],"matching":[19,82],"semantics":[20,83],"determine":[21],"how":[22],"compose":[24],"events":[25],"into":[26],"The":[28],"expressive":[29],"power":[30],"of":[31,43,80,100,110,129,137],"state-of-the-art":[32,143],"streaming":[33],"systems":[34],"remains":[35],"limited":[36],"since":[37],"they":[38,48,58],"do":[39],"not":[40],"support":[41],"many":[42],"these":[44,67,101],"semantics.":[45,102],"Worse":[46],"yet,":[47,88],"suffer":[49],"long":[51],"delays":[52],"high":[54],"memory":[55,139],"costs":[56],"because":[57],"maintain":[59],"aggregates":[60,92,111],"at":[61,93],"a":[62,77],"fine":[63],"granularity.":[64],"To":[65],"overcome":[66],"limitations,":[68],"our":[69],"Coarse-Grained":[70],"Event":[71],"Trend":[72],"Aggregation":[73],"(Cogra)":[74],"approach":[75],"supports":[76],"rich":[78],"variety":[79],"within":[84],"one":[85],"system.":[86],"Better":[87],"Cogra":[89,106,123],"incrementally":[90],"maintains":[91],"the":[94,108],"coarsest":[95],"granularity":[96],"possible":[97],"for":[98],"each":[99],"In":[103],"this":[104],"way,":[105],"minimizes":[107],"number":[109],"--":[112],"reducing":[113],"both":[114],"time":[115],"space":[117],"complexity.":[118],"Our":[119],"experiments":[120],"demonstrate":[121],"that":[122],"achieves":[124],"up":[125,133],"six":[127],"orders":[128,136],"magnitude":[130,138],"speed-up":[131],"seven":[135],"reduction":[140],"compared":[141],"approaches.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}