{"id":"https://openalex.org/W4306875666","doi":"https://doi.org/10.1007/s10796-022-10344-8","title":"Maximal Mixed-Drove Co-occurrence Patterns","display_name":"Maximal Mixed-Drove Co-occurrence Patterns","publication_year":2022,"publication_date":"2022-10-20","ids":{"openalex":"https://openalex.org/W4306875666","doi":"https://doi.org/10.1007/s10796-022-10344-8"},"language":"en","primary_location":{"id":"doi:10.1007/s10796-022-10344-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10796-022-10344-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10796-022-10344-8.pdf","source":{"id":"https://openalex.org/S181659395","display_name":"Information Systems Frontiers","issn_l":"1387-3326","issn":["1387-3326","1572-9419"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information Systems Frontiers","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10796-022-10344-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065038855","display_name":"Witold Andrzejewski","orcid":"https://orcid.org/0000-0001-9486-929X"},"institutions":[{"id":"https://openalex.org/I46597724","display_name":"Pozna\u0144 University of Technology","ror":"https://ror.org/00p7p3302","country_code":"PL","type":"education","lineage":["https://openalex.org/I46597724"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Witold Andrzejewski","raw_affiliation_strings":["Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Wielkopolska, Poland"],"affiliations":[{"raw_affiliation_string":"Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Wielkopolska, Poland","institution_ids":["https://openalex.org/I46597724"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022879000","display_name":"Pawe\u0142 Boi\u0144ski","orcid":"https://orcid.org/0000-0003-4914-9394"},"institutions":[{"id":"https://openalex.org/I46597724","display_name":"Pozna\u0144 University of Technology","ror":"https://ror.org/00p7p3302","country_code":"PL","type":"education","lineage":["https://openalex.org/I46597724"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Pawel Boinski","raw_affiliation_strings":["Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Wielkopolska, Poland"],"affiliations":[{"raw_affiliation_string":"Faculty of Computing and Telecommunications, Poznan University of Technology, Piotrowo 2, Poznan, 60-965, Wielkopolska, Poland","institution_ids":["https://openalex.org/I46597724"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5065038855"],"corresponding_institution_ids":["https://openalex.org/I46597724"],"apc_list":{"value":2290,"currency":"EUR","value_usd":2890},"apc_paid":{"value":2290,"currency":"EUR","value_usd":2890},"fwci":0.636,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.75034045,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"25","issue":"5","first_page":"2005","last_page":"2028"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9979000091552734,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.7880817651748657},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.7671940326690674},{"id":"https://openalex.org/keywords/element","display_name":"Element (criminal law)","score":0.6499770879745483},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5487906336784363},{"id":"https://openalex.org/keywords/apriori-algorithm","display_name":"Apriori algorithm","score":0.4300463795661926},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4207318425178528},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3322712779045105},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2756724953651428},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.26515644788742065}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7880817651748657},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.7671940326690674},{"id":"https://openalex.org/C200288055","wikidata":"https://www.wikidata.org/wiki/Q2621792","display_name":"Element (criminal law)","level":2,"score":0.6499770879745483},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5487906336784363},{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.4300463795661926},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4207318425178528},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3322712779045105},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2756724953651428},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.26515644788742065},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10796-022-10344-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10796-022-10344-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10796-022-10344-8.pdf","source":{"id":"https://openalex.org/S181659395","display_name":"Information Systems Frontiers","issn_l":"1387-3326","issn":["1387-3326","1572-9419"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information Systems Frontiers","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:infosf:v:25:y:2023:i:5:d:10.1007_s10796-022-10344-8","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s10796-022-10344-8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s10796-022-10344-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10796-022-10344-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10796-022-10344-8.pdf","source":{"id":"https://openalex.org/S181659395","display_name":"Information Systems Frontiers","issn_l":"1387-3326","issn":["1387-3326","1572-9419"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information Systems Frontiers","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320322481","display_name":"Politechnika Pozna\u0144ska","ror":"https://ror.org/00p7p3302"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4306875666.pdf","grobid_xml":"https://content.openalex.org/works/W4306875666.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1506285740","https://openalex.org/W1515526911","https://openalex.org/W1525898800","https://openalex.org/W1574667428","https://openalex.org/W1964570589","https://openalex.org/W1991086014","https://openalex.org/W1994963368","https://openalex.org/W2091287849","https://openalex.org/W2120117766","https://openalex.org/W2121095871","https://openalex.org/W2136171062","https://openalex.org/W2139644595","https://openalex.org/W2156930951","https://openalex.org/W2161006174","https://openalex.org/W2163926517","https://openalex.org/W2337480916","https://openalex.org/W2468789976","https://openalex.org/W2585091585","https://openalex.org/W2763111993","https://openalex.org/W2890279180","https://openalex.org/W2979821408","https://openalex.org/W3088214936","https://openalex.org/W3135474149","https://openalex.org/W3196180760"],"related_works":["https://openalex.org/W2059333989","https://openalex.org/W2355391054","https://openalex.org/W4299529113","https://openalex.org/W2385229093","https://openalex.org/W2171877427","https://openalex.org/W2367209111","https://openalex.org/W2118198359","https://openalex.org/W2348237075","https://openalex.org/W2357632367","https://openalex.org/W2353467354"],"abstract_inverted_index":{"Abstract":[0],"One":[1],"of":[2,6,18,82,92,116,154],"the":[3,10,35,54,74],"interesting":[4],"types":[5,17],"spatio-temporal":[7],"patterns":[8,56,81],"is":[9,76],"Mixed-Drove":[11,100],"Co-occurrence":[12,101],"Pattern":[13],"(MDCOP),":[14],"which":[15,110],"represents":[16],"objects":[19],"frequently":[20],"located":[21],"together":[22],"in":[23,63,143],"both":[24],"space":[25],"and":[26,57,134],"time.":[27],"To":[28],"discover":[29,122],"such":[30],"patterns,":[31],"methods":[32],"based":[33],"on":[34,132],"well-known":[36],"Apriori":[37,114],"strategy":[38,115],"are":[39],"widely":[40],"used.":[41],"They":[42],"involve":[43],"determining":[44],"multi-element":[45],"MDCOPs":[46],"by":[47],"building":[48],"them":[49],"up":[50],"iteratively":[51],"starting":[52],"with":[53,150],"two-element":[55],"then":[58],"successively":[59],"adding":[60],"another":[61],"element":[62],"each":[64],"iteration.":[65],"This":[66],"approach":[67],"can":[68,121],"be":[69],"very":[70],"costly,":[71],"particularly":[72],"when":[73],"data":[75],"dense":[77,146],"enough":[78],"to":[79],"form":[80],"significant":[83],"size.":[84],"In":[85],"this":[86],"paper,":[87],"we":[88],"introduce":[89],"a":[90,93,98,106],"definition":[91],"new":[94,107],"pattern":[95,124],"type":[96],"called":[97],"Maximal":[99],"Pattern.":[102],"We":[103],"also":[104],"propose":[105],"algorithm":[108],"MAXMDCOP-Miner,":[109],"resigns":[111],"from":[112],"popular":[113],"generating":[117],"candidates":[118],"and,":[119],"therefore,":[120],"long":[123],"without":[125],"processing":[126],"all":[127],"their":[128],"subsets.":[129],"Experiments":[130],"performed":[131],"synthetic":[133],"real":[135],"datasets":[136,147],"show":[137],"that":[138],"MAXMDCOP-Miner":[139],"has":[140],"high":[141],"performance,":[142],"particular":[144],"for":[145],"or":[148,156],"tasks":[149],"low":[151],"user-defined":[152],"thresholds":[153],"spatial":[155],"time":[157],"prevalence.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}