{"id":"https://openalex.org/W4400957433","doi":"https://doi.org/10.15388/24-infor566","title":"An Improved Algorithm for Extracting Frequent Gradual Patterns","display_name":"An Improved Algorithm for Extracting Frequent Gradual Patterns","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400957433","doi":"https://doi.org/10.15388/24-infor566"},"language":"en","primary_location":{"id":"doi:10.15388/24-infor566","is_oa":true,"landing_page_url":"http://dx.doi.org/10.15388/24-infor566","pdf_url":"https://informatica.vu.lt/journal/INFORMATICA/article/1342/file/pdf","source":{"id":"https://openalex.org/S57195646","display_name":"Informatica","issn_l":"0868-4952","issn":["0868-4952","1822-8844"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://informatica.vu.lt/journal/INFORMATICA/article/1342/file/pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076590590","display_name":"Edith B\u00e9lise Kenmogne","orcid":"https://orcid.org/0000-0002-0149-4167"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Edith Belise Kenmogne","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105019470","display_name":"Idriss Tetakouchom","orcid":"https://orcid.org/0000-0003-3413-0981"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Idriss Tetakouchom","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-3413-0981","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077202751","display_name":"Cl\u00e9mentin Tayou Djamegni","orcid":"https://orcid.org/0000-0002-2231-3281"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cl\u00e9mentin Tayou Djamegni","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023748761","display_name":"Roger Nkambou","orcid":"https://orcid.org/0000-0002-8632-6997"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Roger Nkambou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5035703412","display_name":"Tabueu Fotso Laurent Cabrel","orcid":"https://orcid.org/0000-0001-7057-2221"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Laurent Cabrel Tabueu Fotso","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5076590590"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2381,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.49559326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"577","last_page":"600"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.989300012588501,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.989300012588501,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9890000224113464,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9869999885559082,"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/computer-science","display_name":"Computer science","score":0.4768337309360504},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4443019926548004},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3660484850406647},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35494518280029297}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4768337309360504},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4443019926548004},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3660484850406647},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35494518280029297}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.15388/24-infor566","is_oa":true,"landing_page_url":"http://dx.doi.org/10.15388/24-infor566","pdf_url":"https://informatica.vu.lt/journal/INFORMATICA/article/1342/file/pdf","source":{"id":"https://openalex.org/S57195646","display_name":"Informatica","issn_l":"0868-4952","issn":["0868-4952","1822-8844"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.15388/24-infor566","is_oa":true,"landing_page_url":"http://dx.doi.org/10.15388/24-infor566","pdf_url":"https://informatica.vu.lt/journal/INFORMATICA/article/1342/file/pdf","source":{"id":"https://openalex.org/S57195646","display_name":"Informatica","issn_l":"0868-4952","issn":["0868-4952","1822-8844"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Informatica","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4400957433.pdf"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1525813043","https://openalex.org/W1761828465","https://openalex.org/W2026652666","https://openalex.org/W2100176599","https://openalex.org/W2110598277","https://openalex.org/W2566763598","https://openalex.org/W2575878511","https://openalex.org/W2979718624","https://openalex.org/W3012665221","https://openalex.org/W3041811420","https://openalex.org/W3085729720","https://openalex.org/W3091288722","https://openalex.org/W3141985232","https://openalex.org/W3166390316","https://openalex.org/W4200008323","https://openalex.org/W4223423134","https://openalex.org/W4309530751","https://openalex.org/W4320176732","https://openalex.org/W4378083939"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Frequent":[0],"gradual":[1,36,82],"pattern":[2,20],"extraction":[3,33,80],"is":[4,102,145],"an":[5],"important":[6],"problem":[7,67],"in":[8,41,56,116],"computer":[9],"science":[10],"widely":[11],"studied":[12],"by":[13,96],"the":[14,32,35,66,79,88,114,125,129,133,138,141,160],"data":[15],"mining":[16],"community.":[17],"Such":[18],"a":[19,22,27,75,103],"reflects":[21],"co-variation":[23],"between":[24],"attributes":[25],"of":[26,31,34,58,68,81,90,105,113,118,140],"database.":[28],"The":[29,48,111],"applications":[30],"patterns":[37,53,85],"concern":[38],"several":[39],"fields,":[40],"particular,":[42],"biology,":[43],"finances,":[44],"health":[45],"and":[46,60,83,93,121,124,136,155],"metrology.":[47],"algorithms":[49,154],"for":[50,78],"extracting":[51],"these":[52],"are":[54],"greedy":[55],"terms":[57,117],"memory":[59,122],"computational":[61],"resources.":[62],"This":[63,72],"clearly":[64],"poses":[65],"improving":[69],"their":[70],"performance.":[71],"paper":[73],"proposes":[74],"new":[76],"approach":[77],"frequent":[84,98],"based":[86],"on":[87],"reduction":[89],"candidate":[91],"generation":[92],"processing":[94],"costs":[95],"exploiting":[97],"itemsets":[99],"whose":[100],"size":[101],"power":[104],"two":[106],"to":[107],"generate":[108],"all":[109],"candidates.":[110],"analysis":[112],"complexity,":[115],"CPU":[119],"time":[120],"usage,":[123],"experiments":[126],"show":[127],"that":[128],"obtained":[130],"algorithm":[131],"outperforms":[132],"previous":[134,153],"ones":[135],"confirms":[137],"interest":[139],"proposed":[142],"approach.":[143],"It":[144],"sometimes":[146],"at":[147,157],"least":[148],"5":[149],"times":[150],"faster":[151],"than":[152],"requires":[156],"most":[158],"half":[159],"memory.":[161]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-11T06:11:40.159057","created_date":"2025-10-10T00:00:00"}