{"id":"https://openalex.org/W1972445403","doi":"https://doi.org/10.1117/12.2041342","title":"Progressively consolidating historical visual explorations for new discoveries","display_name":"Progressively consolidating historical visual explorations for new discoveries","publication_year":2013,"publication_date":"2013-12-23","ids":{"openalex":"https://openalex.org/W1972445403","doi":"https://doi.org/10.1117/12.2041342","mag":"1972445403"},"language":"en","primary_location":{"id":"doi:10.1117/12.2041342","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2041342","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-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/A5089128337","display_name":"Kaiyu Zhao","orcid":null},"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":true,"raw_author_name":"Kaiyu Zhao","raw_affiliation_strings":["Worcester Polytechnic Institute (United States)","Worcester Polytechnic Institute,United States"],"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute (United States)","institution_ids":["https://openalex.org/I107077323"]},{"raw_affiliation_string":"Worcester Polytechnic Institute,United States","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102773082","display_name":"Matthew O. Ward","orcid":"https://orcid.org/0000-0002-3080-2579"},"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":"Matthew O. Ward","raw_affiliation_strings":["Worcester Polytechnic Institute (United States)","Worcester Polytechnic Institute,United States"],"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute (United States)","institution_ids":["https://openalex.org/I107077323"]},{"raw_affiliation_string":"Worcester Polytechnic Institute,United States","institution_ids":["https://openalex.org/I107077323"]}]},{"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 (United States)","Worcester Polytechnic Institute,United States"],"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute (United States)","institution_ids":["https://openalex.org/I107077323"]},{"raw_affiliation_string":"Worcester Polytechnic Institute,United States","institution_ids":["https://openalex.org/I107077323"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036952709","display_name":"Huong N. Higgins","orcid":null},"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":"Huong N. Higgins","raw_affiliation_strings":["Worcester Polytechnic Institute (United States)","Worcester Polytechnic Institute,United States"],"affiliations":[{"raw_affiliation_string":"Worcester Polytechnic Institute (United States)","institution_ids":["https://openalex.org/I107077323"]},{"raw_affiliation_string":"Worcester Polytechnic Institute,United States","institution_ids":["https://openalex.org/I107077323"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089128337"],"corresponding_institution_ids":["https://openalex.org/I107077323"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05304916,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9017","issue":null,"first_page":"90170T","last_page":"90170T"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9987000226974487,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9987000226974487,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9986000061035156,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9909999966621399,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.774722695350647},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6146736741065979},{"id":"https://openalex.org/keywords/complement","display_name":"Complement (music)","score":0.6100875735282898},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5887932777404785},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5369925498962402},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5146068334579468},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47824612259864807},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.463864266872406},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.41907137632369995},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.376956582069397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33952176570892334},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3204347491264343},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1563911736011505},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08872094750404358}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.774722695350647},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6146736741065979},{"id":"https://openalex.org/C112313634","wikidata":"https://www.wikidata.org/wiki/Q7886648","display_name":"Complement (music)","level":5,"score":0.6100875735282898},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5887932777404785},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5369925498962402},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5146068334579468},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47824612259864807},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.463864266872406},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.41907137632369995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.376956582069397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33952176570892334},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3204347491264343},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1563911736011505},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08872094750404358},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C188082640","wikidata":"https://www.wikidata.org/wiki/Q1780899","display_name":"Complementation","level":4,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127716648","wikidata":"https://www.wikidata.org/wiki/Q104053","display_name":"Phenotype","level":3,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1117/12.2041342","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2041342","pdf_url":null,"source":{"id":"https://openalex.org/S183492911","display_name":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","issn_l":"0277-786X","issn":["0277-786X","1996-756X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SPIE Proceedings","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.644.3943","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.644.3943","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://davis.wpi.edu/~xmdv/docs/Zhao_VDA2014.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W54446695","https://openalex.org/W605727707","https://openalex.org/W1502567067","https://openalex.org/W1918522533","https://openalex.org/W1981325128","https://openalex.org/W1984107911","https://openalex.org/W2017018978","https://openalex.org/W2038430060","https://openalex.org/W2078638465","https://openalex.org/W2082612735","https://openalex.org/W2083922075","https://openalex.org/W2107260187","https://openalex.org/W2118050072","https://openalex.org/W2120587290","https://openalex.org/W2126470108","https://openalex.org/W2127058057","https://openalex.org/W2132631291","https://openalex.org/W2165966087","https://openalex.org/W2395138788","https://openalex.org/W6602183566","https://openalex.org/W6629941487","https://openalex.org/W6640114403","https://openalex.org/W6645935528","https://openalex.org/W6654696751","https://openalex.org/W6659873680","https://openalex.org/W6671467589","https://openalex.org/W6676196277","https://openalex.org/W6677327956","https://openalex.org/W6677561110","https://openalex.org/W6684643452","https://openalex.org/W6712286786"],"related_works":["https://openalex.org/W2794206341","https://openalex.org/W2013728941","https://openalex.org/W4225274103","https://openalex.org/W2154046714","https://openalex.org/W2189613078","https://openalex.org/W2579659702","https://openalex.org/W2923661510","https://openalex.org/W1574055964","https://openalex.org/W1965329638","https://openalex.org/W2542318691"],"abstract_inverted_index":{"A":[0],"significant":[1],"task":[2],"within":[3],"data":[4,9,28,52,57,98],"mining":[5],"is":[6],"to":[7,47,88,122,146,196,210],"identify":[8],"models":[10,29,58,63,109,132,157,206],"of":[11,25,83,102,104,107,130,137,175,183,214,230],"interest.":[12],"While":[13],"facilitating":[14],"the":[15,27,34,45,51,61,65,92,100,135,148,150,153,156,159,176,188,227],"exploration":[16,185],"tasks,":[17],"most":[18],"visualization":[19],"systems":[20],"do":[21],"not":[22],"make":[23],"use":[24],"all":[26],"that":[30,43,78],"are":[31],"generated":[32,62],"during":[33],"exploration.":[35],"In":[36,144],"this":[37],"paper,":[38],"we":[39],"introduce":[40],"a":[41,71,72,80,128,141,211,223],"system":[42,126,151,221],"allows":[44],"user":[46,93,189],"gain":[48],"insights":[49],"from":[50,204],"space":[53],"progressively":[54],"by":[55],"forming":[56],"and":[59,85,96,133,161,173,186],"consolidating":[60],"on":[64],"fly.":[66],"Each":[67],"model":[68,139],"can":[69,194,207],"be":[70,208],"computationally":[73],"extracted":[74],"or":[75,116,119],"user-defined":[76],"subset":[77],"contains":[79],"certain":[81],"degree":[82,101],"interest":[84,103],"might":[86],"lead":[87,195],"some":[89,105,108],"discoveries.":[90,198],"When":[91],"generates":[94],"more":[95,97],"models,":[99,149],"portion":[106],"will":[110,117],"either":[111],"grow":[112],"(indicating":[113],"higher":[114],"occurrence)":[115],"fluctuate":[118],"decrease":[120],"(corresponding":[121],"lower":[123],"occurrence).":[124],"Our":[125],"maintains":[127],"collection":[129,160],"such":[131],"accumulates":[134],"interestingness":[136,180],"each":[138,166,171],"into":[140],"consolidated":[142],"model.":[143],"order":[145],"consolidate":[147],"summarizes":[152],"associations":[154],"between":[155],"in":[158,222],"identifies":[162],"support":[163,216],"(models":[164,169],"reinforce":[165],"other),":[167,172],"complementary":[168],"complement":[170],"overlap":[174],"models.":[177],"The":[178],"accumulated":[179],"keeps":[181],"track":[182],"historical":[184],"helps":[187],"summarize":[190],"their":[191],"findings":[192],"which":[193],"new":[197],"This":[199],"mechanism":[200],"for":[201],"integrating":[202],"results":[203],"multiple":[205],"applied":[209],"wide":[212],"range":[213],"decision":[215],"systems.":[217],"We":[218],"demonstrate":[219],"our":[220],"case":[224],"study":[225],"involving":[226],"financial":[228],"status":[229],"US":[231],"companies.":[232]},"counts_by_year":[],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
