{"id":"https://openalex.org/W4309651992","doi":"https://doi.org/10.1145/3557915.3560998","title":"Mining spatiotemporally invariant patterns","display_name":"Mining spatiotemporally invariant patterns","publication_year":2022,"publication_date":"2022-11-01","ids":{"openalex":"https://openalex.org/W4309651992","doi":"https://doi.org/10.1145/3557915.3560998"},"language":"en","primary_location":{"id":"doi:10.1145/3557915.3560998","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3557915.3560998","pdf_url":null,"source":{"id":"https://openalex.org/S4363608995","display_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"conference-paper","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/A5049068292","display_name":"Luca Colomba","orcid":"https://orcid.org/0000-0003-2911-4522"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Colomba","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001746215","display_name":"Luca Cagliero","orcid":"https://orcid.org/0000-0002-7185-5247"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Luca Cagliero","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074057809","display_name":"Paolo Garza","orcid":"https://orcid.org/0000-0002-1263-7522"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Politecnico di Torino","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Garza","raw_affiliation_strings":["Politecnico di Torino, Torino, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Politecnico di Torino, Torino, Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":0.2512,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50808129,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9969000220298767,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9884999990463257,"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/invariant","display_name":"Invariant (physics)","score":0.7978426218032837},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7101446390151978},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5156132578849792},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.43658334016799927},{"id":"https://openalex.org/keywords/exploratory-data-analysis","display_name":"Exploratory data analysis","score":0.422130286693573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3991561830043793},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37596553564071655},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19453048706054688}],"concepts":[{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.7978426218032837},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7101446390151978},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5156132578849792},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.43658334016799927},{"id":"https://openalex.org/C120894424","wikidata":"https://www.wikidata.org/wiki/Q1322871","display_name":"Exploratory data analysis","level":2,"score":0.422130286693573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3991561830043793},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37596553564071655},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19453048706054688},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3557915.3560998","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3557915.3560998","pdf_url":null,"source":{"id":"https://openalex.org/S4363608995","display_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.4099999964237213,"display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W148444222","https://openalex.org/W1490018220","https://openalex.org/W2916932086","https://openalex.org/W3098219276","https://openalex.org/W3173197429","https://openalex.org/W3175605680","https://openalex.org/W3213647562"],"related_works":["https://openalex.org/W2140798747","https://openalex.org/W2948169060","https://openalex.org/W2730112582","https://openalex.org/W2110696645","https://openalex.org/W2358580169","https://openalex.org/W2111347279","https://openalex.org/W4399426197","https://openalex.org/W2487211728","https://openalex.org/W2378096925","https://openalex.org/W2485376993"],"abstract_inverted_index":{"Discovering":[0],"patterns":[1,68,91],"that":[2],"represent":[3],"key":[4],"spatial":[5,24],"or":[6,28],"temporal":[7,26],"dependencies":[8,27],"among":[9],"data":[10,15,75],"is":[11],"a":[12,38,87],"well-known":[13],"exploratory":[14],"mining":[16],"task.":[17],"However,":[18],"prior":[19],"works":[20],"either":[21],"separately":[22],"analyze":[23],"and":[25,104,108],"discover":[29],"joint":[30],"spatiotemporal":[31,51,82],"properties":[32],"of":[33,40,45,59,90],"specific":[34],"trajectories":[35],"observed":[36],"over":[37],"region":[39],"interest.":[41],"With":[42],"the":[43,47,73],"goal":[44],"generalizing":[46],"information":[48],"provided":[49],"by":[50],"patterns,":[52],"in":[53,72],"this":[54],"paper":[55],"we":[56],"extract":[57],"sequences":[58],"discrete":[60],"events":[61],"showing":[62],"spatiotemporally":[63],"invariant":[64,81],"properties.":[65],"We":[66,84,95],"seek":[67],"whose":[69],"corresponding":[70],"instances":[71],"source":[74],"differ":[76],"only":[77],"due":[78],"to":[79,101],"an":[80,98],"transformation.":[83],"denote":[85],"such":[86],"new":[88],"type":[89],"as":[92],"SpatioTemporally":[93],"Invariant.":[94],"also":[96],"propose":[97],"efficient":[99],"algorithm":[100],"mine":[102],"STInvs":[103],"validate":[105],"its":[106],"efficiency":[107],"effectiveness":[109],"on":[110],"real":[111],"data.":[112]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}