{"id":"https://openalex.org/W2767961829","doi":"https://doi.org/10.1111/exsy.12250","title":"Clustering short temporal behaviour sequences for customer segmentation using LDA","display_name":"Clustering short temporal behaviour sequences for customer segmentation using LDA","publication_year":2017,"publication_date":"2017-11-07","ids":{"openalex":"https://openalex.org/W2767961829","doi":"https://doi.org/10.1111/exsy.12250","mag":"2767961829"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1111/exsy.12250","pdf_url":null,"source":{"id":"https://openalex.org/S72232612","display_name":"Expert Systems","issn_l":"0266-4720","issn":["0266-4720","1468-0394"],"is_oa":false,"is_in_doaj":false,"host_organization":"https://openalex.org/P4310320503","host_organization_name":"Wiley-Blackwell","host_organization_lineage":["https://openalex.org/P4310320503","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley-Blackwell","Wiley"],"type":"journal"},"license":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5060464364","display_name":"Jobin Wilson","orcid":null},"institutions":[],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Jobin Wilson","raw_affiliation_string":"R8D Department, Flytxt, Trivandrum, India","raw_affiliation_strings":["R8D Department, Flytxt, Trivandrum, India"]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086242686","display_name":"Santanu Chaudhury","orcid":"https://orcid.org/0000-0002-5488-7773"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Santanu Chaudhury","raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India"]},{"author_position":"last","author":{"id":"https://openalex.org/A5066116024","display_name":"Brejesh Lall","orcid":"https://orcid.org/0000-0003-2677-3071"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Brejesh Lall","raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Delhi, New Delhi, India"]}],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5060464364"],"corresponding_institution_ids":[],"apc_list":{"value":3860,"currency":"USD","value_usd":3860,"provenance":"doaj"},"apc_paid":{"value":3860,"currency":"USD","value_usd":3860,"provenance":"doaj"},"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":8,"cited_by_percentile_year":{"min":86,"max":87},"biblio":{"volume":"35","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12384","display_name":"Customer Equity Management and Prediction","score":0.9978,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12384","display_name":"Customer Equity Management and Prediction","score":0.9978,"subfield":{"id":"https://openalex.org/subfields/1406","display_name":"Marketing"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12205","display_name":"Clustering of Time Series Data and Algorithms","score":0.9954,"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/T10154","display_name":"Customer Relationships, Behavior, and Loyalty","score":0.9828,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"keyword":"customer segmentation","score":0.7279},{"keyword":"short temporal behaviour sequences","score":0.4931},{"keyword":"clustering","score":0.4661},{"keyword":"lda","score":0.4636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8441396},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7994909},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.67811525},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.59297204},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5911787},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5907755},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.5318757},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.45174336},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.44741762},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.44658545},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.43733323},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4171982},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.41099474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37928656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32367754},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0929932},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C136264566","wikidata":"https://www.wikidata.org/wiki/Q159810","display_name":"Economy","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C44870925","wikidata":"https://www.wikidata.org/wiki/Q37547","display_name":"Astrophysics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1111/exsy.12250","pdf_url":null,"source":{"id":"https://openalex.org/S72232612","display_name":"Expert Systems","issn_l":"0266-4720","issn":["0266-4720","1468-0394"],"is_oa":false,"is_in_doaj":false,"host_organization":"https://openalex.org/P4310320503","host_organization_name":"Wiley-Blackwell","host_organization_lineage":["https://openalex.org/P4310320503","https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley-Blackwell","Wiley"],"type":"journal"},"license":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.74,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, justice, and strong institutions"}],"grants":[],"referenced_works_count":23,"referenced_works":["https://openalex.org/W1537400602","https://openalex.org/W1543048855","https://openalex.org/W1980122825","https://openalex.org/W1985125789","https://openalex.org/W1987971958","https://openalex.org/W1996794795","https://openalex.org/W1997136459","https://openalex.org/W2018040777","https://openalex.org/W2018546346","https://openalex.org/W2022367269","https://openalex.org/W2038854792","https://openalex.org/W2039333445","https://openalex.org/W2041517243","https://openalex.org/W2043281479","https://openalex.org/W2068687483","https://openalex.org/W2077814585","https://openalex.org/W2078663894","https://openalex.org/W2097747115","https://openalex.org/W2099088086","https://openalex.org/W2104168998","https://openalex.org/W2133990480","https://openalex.org/W2164500538","https://openalex.org/W2495384057"],"related_works":["https://openalex.org/W2769501189","https://openalex.org/W4315588616","https://openalex.org/W4312773271","https://openalex.org/W2888805565","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W3005513013","https://openalex.org/W2611137333","https://openalex.org/W4317422773","https://openalex.org/W4389543811"],"ngrams_url":"https://api.openalex.org/works/W2767961829/ngrams","abstract_inverted_index":{"Abstract":[0],"Customer":[1],"segmentation":[2],"based":[3,111,164],"on":[4,165,193],"temporal":[5,91,115,149],"variation":[6,58],"of":[7,49,53,59,95,117,129,142,151],"subscriber":[8,44,60],"preferences":[9,61,153],"is":[10],"useful":[11],"for":[12],"communication":[13,202],"service":[14,203],"providers":[15],"(CSPs)":[16],"in":[17,34,65,154,183],"applications":[18],"such":[19],"as":[20,37,120],"targeted":[21],"campaign":[22],"design,":[23],"churn":[24],"prediction,":[25],"and":[26,51,86,102,122,145],"fraud":[27],"detection.":[28],"Traditional":[29],"clustering":[30,80,160],"algorithms":[31],"are":[32],"inadequate":[33],"this":[35,66],"context,":[36],"a":[38,43,106,139,199],"multidimensional":[39],"feature":[40],"vector":[41],"represents":[42],"profile":[45],"at":[46],"an":[47],"instant":[48],"time,":[50],"grouping":[52],"subscribers":[54,119,163],"needs":[55],"to":[56,88,113,138,161,180],"consider":[57],"across":[62],"time.":[63],"Clustering":[64],"case":[67],"usually":[68],"requires":[69],"complex":[70],"multivariate":[71],"time":[72,78],"series":[73,79],"analysis\u2010based":[74],"models.":[75],"Because":[76],"conventional":[77],"models":[81],"have":[82],"limitations":[83],"around":[84],"scalability":[85],"ability":[87],"accurately":[89],"represent":[90,114],"behaviour":[92,116],"sequences":[93],"(TBS)":[94],"users,":[96],"that":[97,187],"may":[98],"be":[99],"short,":[100],"noisy,":[101],"non\u2010stationary,":[103],"we":[104,170],"propose":[105],"latent":[107],"Dirichlet":[108],"allocation":[109],"(LDA)":[110],"model":[112,126],"mobile":[118],"compact":[121],"interpretable":[123],"profiles.":[124,168],"Our":[125,191],"makes":[127],"use":[128,158],"the":[130,134,147,176],"structural":[131],"regularity":[132],"within":[133],"observable":[135],"data":[136,196],"corresponding":[137],"large":[140],"number":[141],"user":[143,152],"profiles":[144],"relaxes":[146],"strict":[148],"ordering":[150],"TBS":[155,178],"clustering.":[156],"We":[157],"mean\u2010shift":[159],"segment":[162,189],"their":[166],"discovered":[167,177],"Further,":[169],"mine":[171],"segment\u2010specific":[172],"association":[173],"rules":[174],"from":[175,198],"clusters,":[179],"aid":[181],"marketers":[182],"designing":[184],"intelligent":[185],"campaigns":[186],"match":[188],"preferences.":[190],"experiments":[192],"real":[194],"world":[195],"collected":[197],"popular":[200],"Asian":[201],"provider":[204],"gave":[205],"encouraging":[206],"results.":[207]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2767961829","counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2024-03-27T13:22:52.174855","created_date":"2017-11-17"}