{"id":"https://openalex.org/W4380302445","doi":"https://doi.org/10.1109/icaci58115.2023.10146135","title":"Bundle Expending with Customer Embedding: A Case Study","display_name":"Bundle Expending with Customer Embedding: A Case Study","publication_year":2023,"publication_date":"2023-05-06","ids":{"openalex":"https://openalex.org/W4380302445","doi":"https://doi.org/10.1109/icaci58115.2023.10146135"},"language":"en","primary_location":{"id":"doi:10.1109/icaci58115.2023.10146135","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icaci58115.2023.10146135","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 15th International Conference on Advanced Computational Intelligence (ICACI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5012244756","display_name":"Ahmet Tu\u011frul Bayrak","orcid":"https://orcid.org/0009-0009-6043-2765"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmet Tu\u01e7rul Bayrak","raw_affiliation_strings":["Ata Technology Platforms,Data Science and Innovation,&#x0130;stanbul,Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ata Technology Platforms,Data Science and Innovation,&#x0130;stanbul,Turkey","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036976950","display_name":"Sultan Ceren \u00d6ner","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sultan Ceren \u00d6ner","raw_affiliation_strings":["Ata Technology Platforms,Data Science and Innovation,&#x0130;stanbul,Turkey"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ata Technology Platforms,Data Science and Innovation,&#x0130;stanbul,Turkey","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9945999979972839,"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"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9945999979972839,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9779000282287598,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9628999829292297,"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/apriori-algorithm","display_name":"Apriori algorithm","score":0.7352957725524902},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7092154622077942},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6775531768798828},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.6017811894416809},{"id":"https://openalex.org/keywords/association-rule-learning","display_name":"Association rule learning","score":0.5408236980438232},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5206519961357117},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.4756188690662384},{"id":"https://openalex.org/keywords/customer-relationship-management","display_name":"Customer relationship management","score":0.4654237926006317},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.45932289958000183},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4340812563896179},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3346516788005829},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2680708169937134},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.236229807138443},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13952648639678955}],"concepts":[{"id":"https://openalex.org/C81440476","wikidata":"https://www.wikidata.org/wiki/Q513511","display_name":"Apriori algorithm","level":3,"score":0.7352957725524902},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7092154622077942},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6775531768798828},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6017811894416809},{"id":"https://openalex.org/C193524817","wikidata":"https://www.wikidata.org/wiki/Q386780","display_name":"Association rule learning","level":2,"score":0.5408236980438232},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5206519961357117},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.4756188690662384},{"id":"https://openalex.org/C98825075","wikidata":"https://www.wikidata.org/wiki/Q485643","display_name":"Customer relationship management","level":2,"score":0.4654237926006317},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.45932289958000183},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4340812563896179},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3346516788005829},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2680708169937134},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.236229807138443},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13952648639678955},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icaci58115.2023.10146135","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icaci58115.2023.10146135","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 15th International Conference on Advanced Computational Intelligence (ICACI)","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":25,"referenced_works":["https://openalex.org/W1553696291","https://openalex.org/W1614298861","https://openalex.org/W1828724394","https://openalex.org/W2125761757","https://openalex.org/W2126256482","https://openalex.org/W2152536587","https://openalex.org/W2250879510","https://openalex.org/W2398028996","https://openalex.org/W2399167294","https://openalex.org/W2892546451","https://openalex.org/W2962779279","https://openalex.org/W4220877011","https://openalex.org/W4231069483","https://openalex.org/W4293863207","https://openalex.org/W4294629820","https://openalex.org/W4296886567","https://openalex.org/W4312879486","https://openalex.org/W6633402183","https://openalex.org/W6636510571","https://openalex.org/W6638665372","https://openalex.org/W6678825698","https://openalex.org/W6688897457","https://openalex.org/W6712215407","https://openalex.org/W6712620868","https://openalex.org/W6744386904"],"related_works":["https://openalex.org/W2390051172","https://openalex.org/W2367209111","https://openalex.org/W2351000793","https://openalex.org/W2366790077","https://openalex.org/W2348276166","https://openalex.org/W3034345083","https://openalex.org/W2607264580","https://openalex.org/W1483188779","https://openalex.org/W2383378197","https://openalex.org/W4389611318"],"abstract_inverted_index":{"Today,":[0],"in":[1,93,96,126],"addition":[2],"to":[3,46,110],"the":[4,7,11,41,47,58,77,111],"purchased":[5],"products,":[6],"correct":[8],"recommendations":[9],"of":[10,25],"by-products":[12],"that":[13,88,118],"can":[14],"be":[15],"sold":[16],"with":[17,57,71,76],"these":[18],"products":[19,72,103],"are":[20],"a":[21,52,83],"very":[22],"important":[23],"source":[24],"income":[26],"for":[27,61,130,138],"companies.":[28],"To":[29],"achieve":[30],"this,":[31],"decision-makers":[32],"frequently":[33,91],"apply":[34],"association":[35],"analysis":[36],"methods.":[37],"At":[38],"this":[39,50],"point,":[40],"traditional":[42],"apriori":[43,59],"algorithm":[44,60],"comes":[45],"fore.":[48],"In":[49,66],"study,":[51],"recommendation":[53,94],"system":[54],"is":[55,82,124],"created":[56],"two":[62],"different":[63],"data":[64,128],"sets.":[65],"addition,":[67],"customers":[68],"who":[69],"interact":[70],"have":[73,107],"been":[74,90,108,116],"embedded":[75],"word":[78],"embedding":[79,106,123],"mechanism,":[80],"which":[81],"natural":[84],"language":[85],"processing":[86],"method":[87],"has":[89,115],"used":[92],"systems":[95],"recent":[97],"years.":[98],"Applying":[99],"that,":[100],"similar":[101],"customer":[102,122],"determined":[104],"by":[105],"added":[109],"product":[112],"bundles.":[113],"It":[114],"observed":[117],"expanding":[119],"bundles":[120],"via":[121],"useful":[125],"both":[127],"sets":[129],"some":[131],"cases,":[132],"and":[133],"it":[134],"gives":[135],"promising":[136],"results":[137],"future":[139],"studies.":[140]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
