{"id":"https://openalex.org/W4387186069","doi":"https://doi.org/10.1007/s41019-023-00229-4","title":"A Reinduction-Based Approach for Efficient High Utility Itemset Mining from Incremental Datasets","display_name":"A Reinduction-Based Approach for Efficient High Utility Itemset Mining from Incremental Datasets","publication_year":2023,"publication_date":"2023-09-29","ids":{"openalex":"https://openalex.org/W4387186069","doi":"https://doi.org/10.1007/s41019-023-00229-4"},"language":"en","primary_location":{"id":"doi:10.1007/s41019-023-00229-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-023-00229-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-023-00229-4.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"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":"Data Science and Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s41019-023-00229-4.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017089372","display_name":"Pushp Sra","orcid":null},"institutions":[{"id":"https://openalex.org/I1289461252","display_name":"Indian Space Research Organisation","ror":"https://ror.org/00cwrns71","country_code":"IN","type":"government","lineage":["https://openalex.org/I1289461252","https://openalex.org/I3148377317"]},{"id":"https://openalex.org/I152429107","display_name":"Jawaharlal Nehru University","ror":"https://ror.org/0567v8t28","country_code":"IN","type":"education","lineage":["https://openalex.org/I152429107"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Pushp Sra","raw_affiliation_strings":["ISRO Inertial Systems Unit, Indian Space Research Organisation, Thiruvananthapuram, Kerala, India","School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"ISRO Inertial Systems Unit, Indian Space Research Organisation, Thiruvananthapuram, Kerala, India","institution_ids":["https://openalex.org/I1289461252"]},{"raw_affiliation_string":"School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India","institution_ids":["https://openalex.org/I152429107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037033692","display_name":"Satish Chand","orcid":"https://orcid.org/0000-0002-5250-9074"},"institutions":[{"id":"https://openalex.org/I152429107","display_name":"Jawaharlal Nehru University","ror":"https://ror.org/0567v8t28","country_code":"IN","type":"education","lineage":["https://openalex.org/I152429107"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Satish Chand","raw_affiliation_strings":["School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India"],"affiliations":[{"raw_affiliation_string":"School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India","institution_ids":["https://openalex.org/I152429107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5017089372"],"corresponding_institution_ids":["https://openalex.org/I1289461252","https://openalex.org/I152429107"],"apc_list":null,"apc_paid":null,"fwci":5.5276,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.9609734,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"9","issue":"1","first_page":"73","last_page":"87"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9768000245094299,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9567000269889832,"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":0.8182772397994995},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.7766586542129517},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5243238210678101},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.33027923107147217},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23536711931228638}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8182772397994995},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.7766586542129517},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5243238210678101},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.33027923107147217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23536711931228638}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s41019-023-00229-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-023-00229-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-023-00229-4.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"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":"Data Science and Engineering","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:311f5866752845f78a2fcbbc5151eeb8","is_oa":true,"landing_page_url":"https://doaj.org/article/311f5866752845f78a2fcbbc5151eeb8","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Data Science and Engineering, Vol 9, Iss 1, Pp 73-87 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s41019-023-00229-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s41019-023-00229-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s41019-023-00229-4.pdf","source":{"id":"https://openalex.org/S2486411021","display_name":"Data Science and Engineering","issn_l":"2364-1185","issn":["2364-1185","2364-1541"],"is_oa":true,"is_in_doaj":true,"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":"Data Science and Engineering","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Responsible consumption and production","score":0.41999998688697815,"id":"https://metadata.un.org/sdg/12"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387186069.pdf"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W186603837","https://openalex.org/W1963619261","https://openalex.org/W2010528952","https://openalex.org/W2059464296","https://openalex.org/W2090527766","https://openalex.org/W2094830079","https://openalex.org/W2099398039","https://openalex.org/W2115274736","https://openalex.org/W2125352627","https://openalex.org/W2143428105","https://openalex.org/W2151028259","https://openalex.org/W2161637667","https://openalex.org/W2162571043","https://openalex.org/W2406806423","https://openalex.org/W2604029285","https://openalex.org/W2624037023","https://openalex.org/W2756096685","https://openalex.org/W2909787805","https://openalex.org/W2980978612","https://openalex.org/W3035808318","https://openalex.org/W4304691967","https://openalex.org/W4386094585"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W2382290278","https://openalex.org/W2350741829","https://openalex.org/W2530322880","https://openalex.org/W1596801655","https://openalex.org/W2359140296"],"abstract_inverted_index":{"Abstract":[0],"High":[1],"utility":[2,22,60,139],"itemset":[3,88,122],"mining":[4,79,137],"is":[5,40],"a":[6,21,26,82,114,133],"crucial":[7],"research":[8],"area":[9],"that":[10,19,34,46,112,148],"focuses":[11],"on":[12,58],"identifying":[13],"combinations":[14,72],"of":[15,97,121,152],"itemsets":[16,126,140],"from":[17,127,141],"databases":[18,36,143],"possess":[20],"value":[23,61],"higher":[24],"than":[25],"user-specified":[27],"threshold.":[28],"However,":[29],"most":[30],"existing":[31,54],"algorithms":[32,55,80],"assume":[33],"the":[35,59,69,94,106,119,150,153],"are":[37,47],"static,":[38],"which":[39],"not":[41,92],"realistic":[42],"for":[43,87,136],"real-life":[44],"datasets":[45],"continuously":[48],"growing":[49],"with":[50],"new":[51],"data.":[52],"Furthermore,":[53],"only":[56],"rely":[57],"to":[62,67,85,117],"identify":[63],"relevant":[64],"itemsets,":[65],"leading":[66],"even":[68],"earliest":[70],"occurring":[71],"being":[73],"produced":[74],"as":[75],"output.":[76],"Although":[77],"some":[78],"adopt":[81],"support-based":[83],"approach":[84,135],"account":[86],"frequency,":[89],"they":[90],"do":[91],"consider":[93],"temporal":[95],"nature":[96],"itemsets.":[98],"To":[99],"address":[100],"these":[101],"challenges,":[102],"this":[103],"paper":[104,131],"proposes":[105],"Scented":[107],"Utility":[108],"Miner":[109],"(SUM)":[110],"algorithm":[111],"uses":[113],"reinduction":[115],"strategy":[116],"track":[118],"recency":[120],"occurrence":[123],"and":[124,144],"mine":[125],"incremental":[128],"databases.":[129],"The":[130],"provides":[132],"novel":[134],"high":[138],"dynamic":[142],"presents":[145],"several":[146],"experiments":[147],"demonstrate":[149],"effectiveness":[151],"proposed":[154],"approach.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
