{"id":"https://openalex.org/W2838032619","doi":"https://doi.org/10.1145/3216122.3229860","title":"Modeling Customers and Products with Word Embeddings from Receipt Data","display_name":"Modeling Customers and Products with Word Embeddings from Receipt Data","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2838032619","doi":"https://doi.org/10.1145/3216122.3229860","mag":"2838032619"},"language":"en","primary_location":{"id":"doi:10.1145/3216122.3229860","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3216122.3229860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd International Database Engineering &amp; Applications Symposium on   - IDEAS 2018","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://tud.qucosa.de/id/qucosa%3A80633","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077087558","display_name":"Lucas Woltmann","orcid":"https://orcid.org/0000-0003-0720-8878"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Lucas Woltmann","raw_affiliation_strings":["Database Systems Group, Technische Universit\u00e4t Dresden, Dresden, Germany"],"affiliations":[{"raw_affiliation_string":"Database Systems Group, Technische Universit\u00e4t Dresden, Dresden, Germany","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000229374","display_name":"Maik Thiele","orcid":"https://orcid.org/0000-0002-1665-977X"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maik Thiele","raw_affiliation_strings":["Database Systems Group, Technische Universit\u00e4t Dresden, Dresden, Germany"],"affiliations":[{"raw_affiliation_string":"Database Systems Group, Technische Universit\u00e4t Dresden, Dresden, Germany","institution_ids":["https://openalex.org/I78650965"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063512642","display_name":"Wolfgang Lehner","orcid":"https://orcid.org/0000-0001-8107-2775"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Wolfgang Lehner","raw_affiliation_strings":["Database Systems Group, Technische Universit\u00e4t Dresden, Dresden, Germany"],"affiliations":[{"raw_affiliation_string":"Database Systems Group, Technische Universit\u00e4t Dresden, Dresden, Germany","institution_ids":["https://openalex.org/I78650965"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077087558"],"corresponding_institution_ids":["https://openalex.org/I78650965"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.07316222,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"246","last_page":"252"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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":0.9998000264167786,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9977999925613403,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9966999888420105,"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":0.7919144630432129},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.7427802681922913},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.7089978456497192},{"id":"https://openalex.org/keywords/receipt","display_name":"Receipt","score":0.6852626800537109},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.643076479434967},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5697277784347534},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5696873664855957},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.5546275973320007},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.49842143058776855},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.4896679222583771},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.479109525680542},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4316132068634033},{"id":"https://openalex.org/keywords/word-of-mouth","display_name":"Word of mouth","score":0.4196368157863617},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.38751354813575745},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.356396347284317},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3371170163154602},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.24365687370300293},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.22841909527778625},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.11710572242736816},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.08423352241516113}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7919144630432129},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.7427802681922913},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.7089978456497192},{"id":"https://openalex.org/C2778979077","wikidata":"https://www.wikidata.org/wiki/Q330190","display_name":"Receipt","level":2,"score":0.6852626800537109},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.643076479434967},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5697277784347534},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5696873664855957},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.5546275973320007},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.49842143058776855},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.4896679222583771},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.479109525680542},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4316132068634033},{"id":"https://openalex.org/C137913393","wikidata":"https://www.wikidata.org/wiki/Q15737157","display_name":"Word of mouth","level":2,"score":0.4196368157863617},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.38751354813575745},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.356396347284317},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3371170163154602},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.24365687370300293},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.22841909527778625},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.11710572242736816},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.08423352241516113},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3216122.3229860","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3216122.3229860","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd International Database Engineering &amp; Applications Symposium on   - IDEAS 2018","raw_type":"proceedings-article"},{"id":"pmh:oai:qucosa:de:qucosa:80633","is_oa":true,"landing_page_url":"https://tud.qucosa.de/id/qucosa%3A80633","pdf_url":null,"source":{"id":"https://openalex.org/S4377196312","display_name":"Qucosa (Saxon State and University Library Dresden)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I3132420320","host_organization_name":"SLUB Dresden","host_organization_lineage":["https://openalex.org/I3132420320"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"doc-type:Text"}],"best_oa_location":{"id":"pmh:oai:qucosa:de:qucosa:80633","is_oa":true,"landing_page_url":"https://tud.qucosa.de/id/qucosa%3A80633","pdf_url":null,"source":{"id":"https://openalex.org/S4377196312","display_name":"Qucosa (Saxon State and University Library Dresden)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I3132420320","host_organization_name":"SLUB Dresden","host_organization_lineage":["https://openalex.org/I3132420320"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"doc-type:Text"},"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W155952036","https://openalex.org/W1502364872","https://openalex.org/W1503398984","https://openalex.org/W1524342674","https://openalex.org/W1978394996","https://openalex.org/W2061873838","https://openalex.org/W2073722401","https://openalex.org/W2095705004","https://openalex.org/W2126854223","https://openalex.org/W2153579005","https://openalex.org/W2252215182","https://openalex.org/W2404417588","https://openalex.org/W2493916176","https://openalex.org/W2500403796","https://openalex.org/W2950133940","https://openalex.org/W3099726625","https://openalex.org/W4233760227","https://openalex.org/W4239210031","https://openalex.org/W4300175872","https://openalex.org/W4301213493"],"related_works":["https://openalex.org/W2364011232","https://openalex.org/W2915320150","https://openalex.org/W1490898716","https://openalex.org/W2348360270","https://openalex.org/W1671466897","https://openalex.org/W3148326824","https://openalex.org/W3125363526","https://openalex.org/W2352792752","https://openalex.org/W1977344913","https://openalex.org/W68701339"],"abstract_inverted_index":{"For":[0],"many":[1],"tasks":[2],"in":[3,103],"market":[4],"research":[5],"it":[6],"is":[7,27,95],"important":[8],"to":[9,99],"model":[10,26],"customers":[11,21,44,88],"and":[12,22,45,70,73,97],"products":[13,23,46],"as":[14],"comparable":[15],"instances.":[16],"Usually,":[17],"the":[18,57,101],"integration":[19],"of":[20,43,59],"into":[24],"one":[25],"not":[28],"trivial.":[29],"In":[30],"this":[31,60],"paper,":[32],"we":[33,62],"will":[34],"detail":[35],"an":[36],"approach":[37,61,94],"for":[38,86],"a":[39,79],"combined":[40],"vector":[41],"space":[42],"based":[47],"on":[48,78],"word":[49,92],"embeddings":[50],"learned":[51],"from":[52],"receipt":[53],"data.":[54],"To":[55],"highlight":[56],"strengths":[58],"propose":[63],"four":[64],"different":[65],"applications:":[66],"recommender":[67],"systems,":[68],"customer":[69],"product":[71],"segmentation":[72],"purchase":[74],"prediction.":[75],"Experimental":[76],"results":[77],"real-world":[80],"dataset":[81],"with":[82],"200M":[83],"order":[84],"receipts":[85],"2M":[87],"show":[89],"that":[90],"our":[91],"embedding":[93],"promising":[96],"helps":[98],"improve":[100],"quality":[102],"these":[104],"applications":[105],"scenarios.":[106]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
