{"id":"https://openalex.org/W2329873145","doi":"https://doi.org/10.5121/ijci.2014.3103","title":"An Efficient Algorithm for Sequence Generation in Data Mining","display_name":"An Efficient Algorithm for Sequence Generation in Data Mining","publication_year":2014,"publication_date":"2014-02-28","ids":{"openalex":"https://openalex.org/W2329873145","doi":"https://doi.org/10.5121/ijci.2014.3103","mag":"2329873145"},"language":"en","primary_location":{"id":"doi:10.5121/ijci.2014.3103","doi":"https://doi.org/10.5121/ijci.2014.3103","is_oa":true,"landing_page_url":"https://doi.org/10.5121/ijci.2014.3103","pdf_url":"https://doi.org/10.5121/ijci.2014.3103","source":{"id":"https://openalex.org/S2764709306","display_name":"International Journal on Cybernetics & Informatics","issn_l":"2277-548X","issn":["2277-548X","2320-8430"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Cybernetics &amp; Informatics","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.5121/ijci.2014.3103","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109446982","display_name":"S. Vijayarani","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I111575329","display_name":"Bharathiar University","ror":"https://ror.org/04fht8c22","country_code":"IN","type":"education","lineage":["https://openalex.org/I111575329"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vijayarani S","raw_affiliation_strings":["M.Phil Research Scholar, Department of computer Science, School of Computer Science & Engineering, Bharathiar University, Coimbatore, Tamilnadu, India","Assistant Professor, Department of computer Science, School of Computer Science & Engineering, Bharathiar University, Coimbatore, Tamilnadu, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"M.Phil Research Scholar, Department of computer Science, School of Computer Science & Engineering, Bharathiar University, Coimbatore, Tamilnadu, India","institution_ids":["https://openalex.org/I111575329"]},{"raw_affiliation_string":"Assistant Professor, Department of computer Science, School of Computer Science & Engineering, Bharathiar University, Coimbatore, Tamilnadu, India","institution_ids":["https://openalex.org/I111575329"]}]},{"author_position":"last","author":{"id":null,"display_name":"Deepa S","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I111575329","display_name":"Bharathiar University","ror":"https://ror.org/04fht8c22","country_code":"IN","type":"education","lineage":["https://openalex.org/I111575329"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Deepa S","raw_affiliation_strings":["Assistant Professor, Department of computer Science, School of Computer Science & Engineering, Bharathiar University, Coimbatore, Tamilnadu, India","M.Phil Research Scholar, Department of computer Science, School of Computer Science & Engineering, Bharathiar University, Coimbatore, Tamilnadu, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Assistant Professor, Department of computer Science, School of Computer Science & Engineering, Bharathiar University, Coimbatore, Tamilnadu, India","institution_ids":["https://openalex.org/I111575329"]},{"raw_affiliation_string":"M.Phil Research Scholar, Department of computer Science, School of Computer Science & Engineering, Bharathiar University, Coimbatore, Tamilnadu, India","institution_ids":["https://openalex.org/I111575329"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I111575329"],"apc_list":null,"apc_paid":null,"fwci":0.505,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.72855717,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":"3","issue":"1","first_page":"21","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":1.0,"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":1.0,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.0,"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.0,"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/sequential-pattern-mining","display_name":"sequential pattern mining","score":0.9120000004768372},{"id":"https://openalex.org/keywords/sequence-generation-algorithm","display_name":"sequence generation algorithm","score":0.9240000247955322},{"id":"https://openalex.org/keywords/gsp","display_name":"GSP","score":0.7089999914169312},{"id":"https://openalex.org/keywords/spades","display_name":"Spades","score":0.9980000257492065},{"id":"https://openalex.org/keywords/prefixspan","display_name":"PrefixSpan","score":0.9980000257492065},{"id":"https://openalex.org/keywords/algorithm-efficiency-comparison","display_name":"algorithm efficiency comparison","score":0.824999988079071},{"id":"https://openalex.org/keywords/retail-transaction-data","display_name":"retail transaction data","score":0.7369999885559082},{"id":"https://openalex.org/keywords/frequent-subsequence-mining","display_name":"frequent subsequence mining","score":0.7350000143051147}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6407151222229004},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5595290660858154},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.557533860206604},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44877728819847107},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5121/ijci.2014.3103","doi":"https://doi.org/10.5121/ijci.2014.3103","is_oa":true,"landing_page_url":"https://doi.org/10.5121/ijci.2014.3103","pdf_url":"https://doi.org/10.5121/ijci.2014.3103","source":{"id":"https://openalex.org/S2764709306","display_name":"International Journal on Cybernetics & Informatics","issn_l":"2277-548X","issn":["2277-548X","2320-8430"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Cybernetics &amp; Informatics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.5121/ijci.2014.3103","doi":"https://doi.org/10.5121/ijci.2014.3103","is_oa":true,"landing_page_url":"https://doi.org/10.5121/ijci.2014.3103","pdf_url":"https://doi.org/10.5121/ijci.2014.3103","source":{"id":"https://openalex.org/S2764709306","display_name":"International Journal on Cybernetics & Informatics","issn_l":"2277-548X","issn":["2277-548X","2320-8430"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal on Cybernetics &amp; Informatics","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2329873145.pdf","grobid_xml":"https://content.openalex.org/works/W2329873145.grobid-xml"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W101834235","https://openalex.org/W123065550","https://openalex.org/W1556091850","https://openalex.org/W1608194207","https://openalex.org/W1978273557","https://openalex.org/W2089323326","https://openalex.org/W2158454296","https://openalex.org/W2168196587","https://openalex.org/W2292070788","https://openalex.org/W2323813842","https://openalex.org/W2476972398","https://openalex.org/W4235621583","https://openalex.org/W4297817349"],"related_works":["https://openalex.org/W2292070788","https://openalex.org/W2147694185","https://openalex.org/W2168196587","https://openalex.org/W2204435252","https://openalex.org/W2138513411","https://openalex.org/W7096813108","https://openalex.org/W2766598781","https://openalex.org/W2122446423","https://openalex.org/W3010396704","https://openalex.org/W2289153466"],"abstract_inverted_index":{"Data":[0],"mining":[1,24,36,56,65,68,121],"is":[2,57,158,164],"the":[3,6,34,60,67,70,90,119,133,154,161],"method":[4],"or":[5],"activity":[7],"of":[8,59,69,78,83,92,122,128,135],"analyzing":[9],"data":[10,23,35,52,108],"from":[11],"different":[12,49],"perspectives":[13],"and":[14,30,46,109,113,143],"summarizing":[15],"it":[16,157],"into":[17],"useful":[18],"information.There":[19],"are":[20,31],"several":[21,86],"major":[22],"techniques":[25],"that":[26,72,160],"have":[27,115],"been":[28,116],"developed":[29,117],"used":[32],"in":[33,51,75,85,125],"projects":[37],"which":[38],"include":[39],"association,":[40],"classification,":[41],"clustering,":[42],"sequential":[43,54,123],"patterns,":[44,95,106],"prediction":[45],"decision":[47],"tree.Among":[48],"tasks":[50],"mining,":[53],"pattern":[55,64],"one":[58],"most":[61],"important":[62],"tasks.Sequential":[63],"involves":[66],"subsequences":[71],"appear":[73],"frequently":[74],"a":[76,81,146],"set":[77],"sequences.It":[79],"has":[80],"variety":[82],"applications":[84],"domains":[87],"such":[88],"as":[89],"analysis":[91],"customer":[93],"purchase":[94],"protein":[96],"sequence":[97,102,137],"analysis,":[98,100,103],"DNA":[99],"gene":[101],"web":[104],"access":[105],"seismologic":[107],"weather":[110],"observations.Various":[111],"models":[112],"algorithms":[114,139],"for":[118],"efficient":[120,166],"patterns":[124],"large":[126],"amount":[127],"data.This":[129],"research":[130],"paper":[131],"analyzes":[132],"efficiency":[134],"three":[136],"generation":[138],"namely":[140],"GSP,":[141],"SPADE":[142],"PrefixSpan":[144,162],"on":[145],"retail":[147],"dataset":[148],"by":[149],"applying":[150],"various":[151],"performance":[152],"factors.From":[153],"experimental":[155],"results,":[156],"observed":[159],"algorithm":[163],"more":[165],"than":[167],"other":[168],"two":[169],"algorithms.":[170]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2016-06-24T00:00:00"}
