{"id":"https://openalex.org/W2511208789","doi":"https://doi.org/10.3233/jifs-169057","title":"A clustering with slope algorithm based\u00a0on\u00a0item similarity","display_name":"A clustering with slope algorithm based\u00a0on\u00a0item similarity","publication_year":2016,"publication_date":"2016-09-09","ids":{"openalex":"https://openalex.org/W2511208789","doi":"https://doi.org/10.3233/jifs-169057","mag":"2511208789"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-169057","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-169057","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"},"type":"article","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/A5066914652","display_name":"Wu Huiyun","orcid":null},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wu Huiyun","raw_affiliation_strings":["Information Office, Shanghai Maritime University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Information Office, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100339104","display_name":"Yuping Wang","orcid":"https://orcid.org/0000-0001-6868-0004"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang Yuping","raw_affiliation_strings":["Information Office, Shanghai Maritime University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Information Office, Shanghai Maritime University, Shanghai, China","institution_ids":["https://openalex.org/I96733725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066914652"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10713235,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"31","issue":"4","first_page":"2177","last_page":"2185"},"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.979200005531311,"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/cluster-analysis","display_name":"Cluster analysis","score":0.811360239982605},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7756921052932739},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.680610179901123},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5991395711898804},{"id":"https://openalex.org/keywords/data-stream-clustering","display_name":"Data stream clustering","score":0.5173329710960388},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.515108048915863},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5052943825721741},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.49924659729003906},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4872928857803345},{"id":"https://openalex.org/keywords/database-transaction","display_name":"Database transaction","score":0.4744739830493927},{"id":"https://openalex.org/keywords/transaction-data","display_name":"Transaction data","score":0.47107091546058655},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.45979779958724976},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4155942499637604},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4114851951599121},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25180792808532715},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.16100695729255676},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1397874355316162},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09167784452438354}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.811360239982605},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7756921052932739},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.680610179901123},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5991395711898804},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.5173329710960388},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.515108048915863},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5052943825721741},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.49924659729003906},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4872928857803345},{"id":"https://openalex.org/C75949130","wikidata":"https://www.wikidata.org/wiki/Q848010","display_name":"Database transaction","level":2,"score":0.4744739830493927},{"id":"https://openalex.org/C127722929","wikidata":"https://www.wikidata.org/wiki/Q7833714","display_name":"Transaction data","level":3,"score":0.47107091546058655},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.45979779958724976},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4155942499637604},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4114851951599121},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25180792808532715},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.16100695729255676},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1397874355316162},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09167784452438354},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","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},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-169057","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-169057","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W189929561","https://openalex.org/W1543951048","https://openalex.org/W1557725856","https://openalex.org/W1559776681","https://openalex.org/W1972532012","https://openalex.org/W1995502855","https://openalex.org/W2002575106","https://openalex.org/W2016121692","https://openalex.org/W2027430431","https://openalex.org/W2036275527","https://openalex.org/W2064853889","https://openalex.org/W2118360154","https://openalex.org/W2137578940","https://openalex.org/W2153293405","https://openalex.org/W2154569688","https://openalex.org/W2170936641","https://openalex.org/W2181965785","https://openalex.org/W2183253799","https://openalex.org/W2337552645","https://openalex.org/W2418423341","https://openalex.org/W2514280761","https://openalex.org/W2537458161","https://openalex.org/W2886661658","https://openalex.org/W3012257125","https://openalex.org/W4285719527","https://openalex.org/W6607691871","https://openalex.org/W6632038870","https://openalex.org/W6682656237","https://openalex.org/W6685077929","https://openalex.org/W6685986551","https://openalex.org/W6726200229","https://openalex.org/W6753898695"],"related_works":["https://openalex.org/W2559422900","https://openalex.org/W3144143113","https://openalex.org/W2491448268","https://openalex.org/W2892323093","https://openalex.org/W4306940721","https://openalex.org/W2181939267","https://openalex.org/W2160785859","https://openalex.org/W3174322327","https://openalex.org/W2394193399","https://openalex.org/W4301002638"],"abstract_inverted_index":{"With":[0],"the":[1,4,7,14,23,68,71,77,81,95,109,114,128,131,140,153,161,172],"development":[2],"of":[3,9,12,16,25,53,70,94,130],"internet":[5],"and":[6,60,118,166],"arrival":[8],"large":[10],"volumes":[11],"data,":[13],"analysis":[15],"transactional":[17,31],"data":[18,26,82,188],"is":[19,74,83,146,164,168,177],"becoming":[20,35],"important":[21],"in":[22,79,102,134],"field":[24],"mining.":[27],"Clustering":[28],"algorithms":[29],"for":[30,186],"trade":[32],"datasets":[33],"are":[34],"a":[36,51,178],"hot":[37],"topic.":[38],"Among":[39],"them,":[40],"clustering":[41,65],"with":[42,122],"slope":[43],"algorithm":[44,73,116,154,176,180],"(CLOPE)":[45],"i":[46],"s":[47],"widely":[48],"used":[49],"as":[50],"result":[52,86,101,132,159],"its":[54],"superior":[55],"performance,":[56],"lower":[57],"memory":[58],"use,":[59],"better":[61,157],"quality":[62,69,129,158,184],"than":[63,171],"other":[64],"algorithms.":[66],"However,":[67],"CLOPE":[72,115],"related":[75],"to":[76,107,138,143],"sequence":[78],"which":[80],"input;":[84],"different":[85,91],"will":[87,126],"be":[88],"clustered":[89],"by":[90],"input":[92],"sequences":[93],"same":[96],"dataset.":[97],"This":[98,175],"can":[99],"even":[100],"poor":[103],"clustering.":[104],"In":[105],"order":[106],"solve":[108],"problem,":[110],"this":[111],"paper":[112],"analyzes":[113],"deeply":[117],"proves":[119],"that":[120,152,181],"records":[121],"more":[123],"items":[124],"ahead":[125],"improve":[127],"greatly":[133],"theory.":[135],"A":[136],"procedure":[137],"preprocess":[139],"dataset":[141],"according":[142],"item":[144],"similarity":[145],"proposed.":[147],"The":[148],"experiment":[149],"results":[150,185],"show":[151],"has":[155],"obviously":[156],"when":[160],"proposed":[162],"method":[163],"used,":[165],"it":[167],"10%":[169],"faster":[170],"traditional":[173],"procedure.":[174],"valid":[179],"produces":[182],"high":[183],"transaction":[187],"sets.":[189]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}