{"id":"https://openalex.org/W2889143062","doi":"https://doi.org/10.1109/tkde.2018.2867185","title":"Scaling the Construction of Wavelet Synopses for Maximum Error Metrics","display_name":"Scaling the Construction of Wavelet Synopses for Maximum Error Metrics","publication_year":2018,"publication_date":"2018-08-28","ids":{"openalex":"https://openalex.org/W2889143062","doi":"https://doi.org/10.1109/tkde.2018.2867185","mag":"2889143062"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2018.2867185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2018.2867185","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5054570106","display_name":"Ioannis Mytilinis","orcid":"https://orcid.org/0000-0002-9901-0721"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Ioannis Mytilinis","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National Technical University of Athens (NTUA), Zografou, Greece"],"raw_orcid":"https://orcid.org/0000-0002-9901-0721","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Technical University of Athens (NTUA), Zografou, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005628435","display_name":"Dimitrios Tsoumakos","orcid":"https://orcid.org/0000-0003-4420-8949"},"institutions":[{"id":"https://openalex.org/I187792471","display_name":"Ionian University","ror":"https://ror.org/01xm4n520","country_code":"GR","type":"education","lineage":["https://openalex.org/I187792471"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dimitrios Tsoumakos","raw_affiliation_strings":["Ionian University, Kerkira, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ionian University, Kerkira, Greece","institution_ids":["https://openalex.org/I187792471"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023526161","display_name":"Nectarios Koziris","orcid":"https://orcid.org/0000-0002-4890-8427"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Nectarios Koziris","raw_affiliation_strings":["Department of Electrical and Computer Engineering, National Technical University of Athens (NTUA), Zografou, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, National Technical University of Athens (NTUA), Zografou, Greece","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.104,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44342074,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"31","issue":"9","first_page":"1794","last_page":"1808"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9904999732971191,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7684592604637146},{"id":"https://openalex.org/keywords/scaling","display_name":"Scaling","score":0.745448112487793},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6282559633255005},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43871569633483887},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3375192880630493},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2805076241493225},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13288530707359314}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7684592604637146},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.745448112487793},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6282559633255005},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43871569633483887},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3375192880630493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2805076241493225},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13288530707359314},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2018.2867185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2018.2867185","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W63681869","https://openalex.org/W1494985239","https://openalex.org/W1524387703","https://openalex.org/W1586098254","https://openalex.org/W1784244685","https://openalex.org/W1822348499","https://openalex.org/W1853916255","https://openalex.org/W1987752353","https://openalex.org/W1993482412","https://openalex.org/W1998244781","https://openalex.org/W2020584928","https://openalex.org/W2021850646","https://openalex.org/W2022858489","https://openalex.org/W2028384865","https://openalex.org/W2039652440","https://openalex.org/W2063512404","https://openalex.org/W2064174652","https://openalex.org/W2064379477","https://openalex.org/W2067304854","https://openalex.org/W2071989194","https://openalex.org/W2079195815","https://openalex.org/W2080785753","https://openalex.org/W2106063091","https://openalex.org/W2106163100","https://openalex.org/W2106834095","https://openalex.org/W2110557355","https://openalex.org/W2122731071","https://openalex.org/W2134017119","https://openalex.org/W2135134185","https://openalex.org/W2153511931","https://openalex.org/W2161463763","https://openalex.org/W2162344883","https://openalex.org/W2401409094","https://openalex.org/W2441222368","https://openalex.org/W2564992522","https://openalex.org/W2611426260","https://openalex.org/W4250854929","https://openalex.org/W4254407475","https://openalex.org/W6602586145","https://openalex.org/W6631677261","https://openalex.org/W6637935085","https://openalex.org/W6638337754","https://openalex.org/W6648171237","https://openalex.org/W6675574014","https://openalex.org/W6676015427","https://openalex.org/W6683614665","https://openalex.org/W6712744764"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2478288626","https://openalex.org/W4391913857"],"abstract_inverted_index":{"Modern":[0],"analytics":[1],"involve":[2],"computations":[3],"over":[4,32,180],"enormous":[5],"numbers":[6],"of":[7,12,25,40,52,100,117,119,141,150,168],"data":[8,13,72,167],"records.":[9],"The":[10],"volume":[11],"and":[14,123,155,177,190],"the":[15,23,33,38,97,101,120,139,184],"stringent":[16],"response-time":[17],"requirements":[18],"place":[19],"increasing":[20],"emphasis":[21],"on":[22,174],"efficiency":[24],"approximate":[26],"query":[27],"processing.":[28],"A":[29],"major":[30],"challenge":[31],"past":[34],"years":[35],"has":[36,63],"been":[37],"construction":[39],"synopses":[41],"that":[42,79,114,130,163,183],"provide":[43,106],"a":[44,53,67,107,135,147],"deterministic":[45],"quality":[46],"guarantee,":[47],"often":[48],"expressed":[49],"in":[50],"terms":[51],"maximum":[54,81],"error":[55,82],"metric.":[56],"By":[57],"approximating":[58],"sharp":[59],"discontinuities,":[60],"wavelet":[61,76,121],"decomposition":[62,122],"proved":[64],"to":[65,105,126,195],"be":[66],"very":[68],"effective":[69],"tool":[70],"for":[71,89,138],"reduction.":[73],"However,":[74],"existing":[75,142],"thresholding":[77],"schemes":[78],"minimize":[80],"metrics":[83],"are":[84],"constrained":[85],"with":[86,166],"impractical":[87],"complexities":[88],"large":[90],"datasets.":[91],"Furthermore,":[92],"they":[93],"cannot":[94],"efficiently":[95],"handle":[96],"multi-dimensional":[98],"version":[99,149],"problem.":[102],"In":[103],"order":[104],"practical":[108],"solution,":[109],"we":[110,132],"develop":[111],"parallel":[112,148],"algorithms":[113,162,186],"take":[115],"advantage":[116],"key-properties":[118],"allocate":[124],"tasks":[125],"multiple":[127],"workers.":[128],"To":[129],"end,":[131],"present":[133],"(i)":[134],"general":[136],"framework":[137],"parallelization":[140],"dynamic":[143],"programming":[144],"algorithms,":[145],"(ii)":[146],"one":[151],"such":[152],"DP":[153],"algorithm,":[154],"(iii)":[156],"two":[157],"highly":[158],"efficient":[159],"distributed":[160],"greedy":[161],"can":[164],"deal":[165],"arbitrary":[169],"dimensionality.":[170],"Our":[171],"extensive":[172],"experiments":[173],"both":[175],"real":[176],"synthetic":[178],"datasets":[179],"Hadoop":[181],"show":[182],"proposed":[185],"achieve":[187],"linear":[188],"scalability":[189],"superior":[191],"running-time":[192],"performance":[193],"compared":[194],"their":[196],"centralized":[197],"counterparts.":[198]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
