{"id":"https://openalex.org/W4414034841","doi":"https://doi.org/10.1145/3705328.3748150","title":"TIM-Rec: Explicit Sparse Feedback on Multi-Item Upselling Recommendations in an Industrial Dataset of Telco Calls","display_name":"TIM-Rec: Explicit Sparse Feedback on Multi-Item Upselling Recommendations in an Industrial Dataset of Telco Calls","publication_year":2025,"publication_date":"2025-09-06","ids":{"openalex":"https://openalex.org/W4414034841","doi":"https://doi.org/10.1145/3705328.3748150"},"language":"en","primary_location":{"id":"doi:10.1145/3705328.3748150","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3705328.3748150","pdf_url":null,"source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3705328.3748150","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114337388","display_name":"Alessandro Sbandi","orcid":"https://orcid.org/0009-0002-8804-2362"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Alessandro Sbandi","raw_affiliation_strings":["TIM S.p.A., Milan, Italy and Sapienza University of Rome, Rome, Italy"],"raw_orcid":"https://orcid.org/0009-0002-8804-2362","affiliations":[{"raw_affiliation_string":"TIM S.p.A., Milan, Italy and Sapienza University of Rome, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074346581","display_name":"Federico Siciliano","orcid":"https://orcid.org/0000-0003-1339-6983"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Federico Siciliano","raw_affiliation_strings":["Sapienza University of Rome, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0003-1339-6983","affiliations":[{"raw_affiliation_string":"Sapienza University of Rome, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044165871","display_name":"Fabrizio Silvestri","orcid":"https://orcid.org/0000-0001-7669-9055"},"institutions":[{"id":"https://openalex.org/I861853513","display_name":"Sapienza University of Rome","ror":"https://ror.org/02be6w209","country_code":"IT","type":"education","lineage":["https://openalex.org/I861853513"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabrizio Silvestri","raw_affiliation_strings":["Sapienza University of Rome, Rome, Italy"],"raw_orcid":"https://orcid.org/0000-0001-7669-9055","affiliations":[{"raw_affiliation_string":"Sapienza University of Rome, Rome, Italy","institution_ids":["https://openalex.org/I861853513"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5114337388"],"corresponding_institution_ids":["https://openalex.org/I861853513"],"apc_list":null,"apc_paid":null,"fwci":2.9051,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92731978,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"865","last_page":"873"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","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/T10203","display_name":"Recommender Systems and Techniques","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/T12384","display_name":"Customer churn and segmentation","score":0.9948999881744385,"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/T11161","display_name":"Consumer Market Behavior and Pricing","score":0.9945999979972839,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7194648385047913},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4066771864891052}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7194648385047913},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4066771864891052}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3705328.3748150","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3705328.3748150","pdf_url":null,"source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.uniroma1.it:11573/1755837","is_oa":true,"landing_page_url":"https://hdl.handle.net/11573/1755837","pdf_url":null,"source":{"id":"https://openalex.org/S4377196107","display_name":"IRIS Research product catalog (Sapienza University of Rome)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.1145/3705328.3748150","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3705328.3748150","pdf_url":null,"source":null,"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Nineteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1548120095","https://openalex.org/W1997136459","https://openalex.org/W2054141820","https://openalex.org/W2086659686","https://openalex.org/W2091158010","https://openalex.org/W2097584193","https://openalex.org/W2101409192","https://openalex.org/W2108862644","https://openalex.org/W2116843572","https://openalex.org/W2120676760","https://openalex.org/W2219888463","https://openalex.org/W2605350416","https://openalex.org/W2783272285","https://openalex.org/W2957293899","https://openalex.org/W2962745591","https://openalex.org/W2963367478","https://openalex.org/W2965893800","https://openalex.org/W2971196067","https://openalex.org/W2972030057","https://openalex.org/W2975938167","https://openalex.org/W2978400229","https://openalex.org/W3034503922","https://openalex.org/W3045200674","https://openalex.org/W3122431341","https://openalex.org/W3130866178","https://openalex.org/W3177364752","https://openalex.org/W4205390421","https://openalex.org/W4221137290","https://openalex.org/W4248416624","https://openalex.org/W4308441097","https://openalex.org/W4400199659","https://openalex.org/W4400689812","https://openalex.org/W4403220074","https://openalex.org/W4403577886","https://openalex.org/W4403601676","https://openalex.org/W4405754319","https://openalex.org/W4406434737"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Upselling":[0],"recommendations":[1,29,100],"play":[2],"a":[3,50,71,155],"critical":[4,51],"role":[5],"in":[6,13,53,63,102,120,162],"improving":[7],"customer":[8,34,82],"engagement":[9],"and":[10,32,65,84,95,105,137],"maximizing":[11],"revenue":[12],"the":[14,38,46,121],"telecommunications":[15],"industry.":[16],"However,":[17],"real-world":[18,91],"data":[19],"on":[20,132],"such":[21],"interactions":[22,92],"often":[23],"presents":[24],"unique":[25],"challenges,":[26,60],"including":[27],"multiple":[28,99],"per":[30],"call":[31],"sparse":[33,106],"feedback,":[35,107],"which":[36],"complicates":[37],"evaluation":[39],"of":[40,45,123,158],"recommender":[41],"systems.":[42],"Our":[43],"review":[44],"existing":[47],"literature":[48],"reveals":[49],"gap":[52],"publicly":[54],"available":[55],"datasets":[56],"that":[57,74],"reflect":[58],"these":[59,76],"limiting":[61],"progress":[62],"developing":[64],"evaluating":[66],"upselling":[67],"strategies.This":[68],"work":[69],"introduces":[70],"novel":[72],"dataset":[73],"captures":[75],"complexities,":[77],"offering":[78],"valuable":[79],"insights":[80],"into":[81],"behavior":[83,111],"recommendation":[85,126,133,144,160],"effectiveness.":[86],"The":[87],"dataset,":[88],"derived":[89],"from":[90,146],"between":[93],"customers":[94],"service":[96],"providers,":[97],"contains":[98],"provided":[101],"individual":[103],"calls":[104],"reflecting":[108],"typical":[109],"user":[110,135],"where":[112],"interest":[113],"may":[114],"be":[115],"low":[116],"or":[117],"unrecorded.To":[118],"aid":[119],"development":[122],"more":[124],"effective":[125],"systems,":[127],"we":[128,141],"provide":[129],"detailed":[130],"statistics":[131],"distributions,":[134],"engagement,":[136],"feedback":[138],"patterns.":[139],"Furthermore,":[140],"benchmark":[142],"various":[143],"models,":[145],"classical":[147],"approaches":[148],"to":[149],"state-of-the-art":[150],"neural":[151],"networks,":[152],"allowing":[153],"for":[154],"comprehensive":[156],"assessment":[157],"their":[159],"accuracy":[161],"this":[163],"challenging":[164],"setting.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}