{"id":"https://openalex.org/W4280629602","doi":"https://doi.org/10.1109/cifer52523.2022.9776210","title":"Understanding Spending Behavior: Recurrent Neural Network Explanation and Interpretation","display_name":"Understanding Spending Behavior: Recurrent Neural Network Explanation and Interpretation","publication_year":2022,"publication_date":"2022-05-01","ids":{"openalex":"https://openalex.org/W4280629602","doi":"https://doi.org/10.1109/cifer52523.2022.9776210"},"language":"en","primary_location":{"id":"doi:10.1109/cifer52523.2022.9776210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cifer52523.2022.9776210","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr)","raw_type":"proceedings-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/A5056533226","display_name":"Charl Maree","orcid":"https://orcid.org/0000-0002-7282-4661"},"institutions":[{"id":"https://openalex.org/I200650556","display_name":"University of Agder","ror":"https://ror.org/03x297z98","country_code":"NO","type":"education","lineage":["https://openalex.org/I200650556"]},{"id":"https://openalex.org/I92008406","display_name":"University of Stavanger","ror":"https://ror.org/02qte9q33","country_code":"NO","type":"education","lineage":["https://openalex.org/I92008406"]}],"countries":["NO"],"is_corresponding":true,"raw_author_name":"Charl Maree","raw_affiliation_strings":["University of Agder,Center for Artificial Intelligence Research,Grimstad,Norway","Center for Artificial Intelligence Research, University of Agder, Grimstad, Norway","Chief Technology Office, Stavanger, Norway"],"affiliations":[{"raw_affiliation_string":"University of Agder,Center for Artificial Intelligence Research,Grimstad,Norway","institution_ids":["https://openalex.org/I200650556"]},{"raw_affiliation_string":"Center for Artificial Intelligence Research, University of Agder, Grimstad, Norway","institution_ids":["https://openalex.org/I200650556"]},{"raw_affiliation_string":"Chief Technology Office, Stavanger, Norway","institution_ids":["https://openalex.org/I92008406"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030608087","display_name":"Christian W. Omlin","orcid":"https://orcid.org/0000-0003-0299-171X"},"institutions":[{"id":"https://openalex.org/I200650556","display_name":"University of Agder","ror":"https://ror.org/03x297z98","country_code":"NO","type":"education","lineage":["https://openalex.org/I200650556"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Christian W. Omlin","raw_affiliation_strings":["University of Agder,Center for Artificial Intelligence Research,Grimstad,Norway","Center for Artificial Intelligence Research, University of Agder, Grimstad, Norway"],"affiliations":[{"raw_affiliation_string":"University of Agder,Center for Artificial Intelligence Research,Grimstad,Norway","institution_ids":["https://openalex.org/I200650556"]},{"raw_affiliation_string":"Center for Artificial Intelligence Research, University of Agder, Grimstad, Norway","institution_ids":["https://openalex.org/I200650556"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056533226"],"corresponding_institution_ids":["https://openalex.org/I200650556","https://openalex.org/I92008406"],"apc_list":null,"apc_paid":null,"fwci":0.982,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.77012459,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.9958000183105469,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.992900013923645,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7210786938667297},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6800219416618347},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.592583954334259},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5662717223167419},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5589193105697632},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.5557788014411926},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47866353392601013},{"id":"https://openalex.org/keywords/state-space","display_name":"State space","score":0.45682504773139954},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4408451318740845},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.38514405488967896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12586775422096252}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7210786938667297},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6800219416618347},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.592583954334259},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5662717223167419},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5589193105697632},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.5557788014411926},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47866353392601013},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.45682504773139954},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4408451318740845},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.38514405488967896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12586775422096252},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cifer52523.2022.9776210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cifer52523.2022.9776210","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W85729824","https://openalex.org/W584910106","https://openalex.org/W2053987251","https://openalex.org/W2064675550","https://openalex.org/W2326140006","https://openalex.org/W2493343568","https://openalex.org/W2588202084","https://openalex.org/W2734775449","https://openalex.org/W2811005285","https://openalex.org/W2914716244","https://openalex.org/W2921122439","https://openalex.org/W2924259991","https://openalex.org/W2962862931","https://openalex.org/W2964200170","https://openalex.org/W2975142265","https://openalex.org/W2981731882","https://openalex.org/W3016401366","https://openalex.org/W3041535480","https://openalex.org/W3100562770","https://openalex.org/W3107413707","https://openalex.org/W3109842401","https://openalex.org/W3133559817","https://openalex.org/W3180026636","https://openalex.org/W3204079133","https://openalex.org/W4206264714","https://openalex.org/W4288311097","https://openalex.org/W6737947904","https://openalex.org/W6765409134","https://openalex.org/W6768198781"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W3010616741","https://openalex.org/W2807240930","https://openalex.org/W4281386417","https://openalex.org/W4319792277","https://openalex.org/W3078840574","https://openalex.org/W4327831767","https://openalex.org/W4310748836","https://openalex.org/W4318159630","https://openalex.org/W3137905681"],"abstract_inverted_index":{"Micro-segmentation":[0],"of":[1,65,74,88,106,118,144,211,219,231],"customers":[2,25],"in":[3,50,69,76,161,197],"the":[4,45,63,72,86,95,103,115,149,159,162,179,184,190,198,209,212,217],"finance":[5,81],"sector":[6],"is":[7],"a":[8,58,107,134,153,204,229],"nontrivial":[9],"task":[10],"and":[11,54,140,222,227],"has":[12,82],"been":[13],"an":[14,123,142],"atypical":[15],"omission":[16],"from":[17,102],"recent":[18],"scientific":[19],"literature.":[20],"Where":[21],"traditional":[22],"segmentation":[23],"classifies":[24],"based":[26],"on":[27,85],"coarse":[28],"features":[29,101,160],"such":[30,79],"as":[31,80],"demographics,":[32],"micro-segmentation":[33,96],"depicts":[34],"more":[35],"nuanced":[36],"differences":[37],"between":[38],"individuals,":[39],"bringing":[40],"forth":[41],"several":[42],"advantages":[43],"including":[44],"potential":[46],"for":[47,137],"improved":[48],"personalization":[49],"financial":[51],"services.":[52],"AI":[53,75],"representation":[55],"learning":[56],"offer":[57],"unique":[59],"opportunity":[60],"to":[61,114,157,182,207,225],"solve":[62],"problem":[64,97],"micro-segmentation.":[66],"Although":[67],"ubiquitous":[68],"many":[70],"industries,":[71],"proliferation":[73],"sensitive":[77],"industries":[78],"become":[83],"contingent":[84],"explainability":[87],"deep":[89],"models.":[90],"We":[91,168],"had":[92],"previously":[93],"solved":[94],"by":[98,132,215],"extracting":[99,133],"temporal":[100,146],"state":[104,163,213],"space":[105,164,214],"recurrent":[108],"neural":[109],"network":[110],"(RNN).":[111],"However,":[112],"due":[113],"inherent":[116],"opacity":[117],"RNNs,":[119],"our":[120,138,145,171],"solution":[121],"lacked":[122],"explanation.":[124],"In":[125],"this":[126,130],"study,":[127],"we":[128,151,202],"address":[129],"issue":[131],"symbolic":[135],"explanation":[136],"model":[139,156],"providing":[141],"interpretation":[143],"features.":[147],"For":[148],"explanation,":[150],"use":[152],"linear":[154,172],"regression":[155,173,221],"reconstruct":[158],"with":[165],"high":[166],"fidelity.":[167],"show":[169],"that":[170,192],"coefficients":[174],"have":[175,187],"not":[176,194],"only":[177],"learned":[178,189],"rules":[180],"used":[181],"recreate":[183],"features,":[185],"but":[186],"also":[188],"relationships":[191],"were":[193],"directly":[195],"evident":[196],"raw":[199],"data.":[200],"Finally,":[201],"propose":[203],"novel":[205],"method":[206],"interpret":[208],"dynamics":[210],"using":[216],"principles":[218],"inverse":[220],"dynamical":[223],"systems":[224],"locate":[226],"label":[228],"set":[230],"attractors.":[232]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
