{"id":"https://openalex.org/W4416016495","doi":"https://doi.org/10.1145/3746252.3761552","title":"Next-Generation Price Recommendation with LLM-Augmented Graph Transformers","display_name":"Next-Generation Price Recommendation with LLM-Augmented Graph Transformers","publication_year":2025,"publication_date":"2025-11-08","ids":{"openalex":"https://openalex.org/W4416016495","doi":"https://doi.org/10.1145/3746252.3761552"},"language":null,"primary_location":{"id":"doi:10.1145/3746252.3761552","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746252.3761552","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3746252.3761552","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5117649498","display_name":"Hadi Mohammadzadeh Abachi","orcid":"https://orcid.org/0009-0007-2329-8355"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Hadi Mohammadzadeh Abachi","raw_affiliation_strings":["Macquarie University, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056293251","display_name":"Amin Beheshti","orcid":"https://orcid.org/0000-0002-5988-5494"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Amin Beheshti","raw_affiliation_strings":["Macquarie University, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117649500","display_name":"Milad Mosharraf","orcid":"https://orcid.org/0009-0002-3133-7960"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Milad Mosharraf","raw_affiliation_strings":["Domain Group, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Domain Group, Sydney, NSW, Australia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117649501","display_name":"Pooyan Asgari","orcid":"https://orcid.org/0009-0002-4873-6562"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pooyan Asgari","raw_affiliation_strings":["Domain Group, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Domain Group, Sydney, NSW, Australia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5117649499","display_name":"Majid Namazi","orcid":"https://orcid.org/0000-0002-9500-4500"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Majid Namazi","raw_affiliation_strings":["Macquarie University, Sydney, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Macquarie University, Sydney, NSW, Australia","institution_ids":["https://openalex.org/I99043593"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5117649498"],"corresponding_institution_ids":["https://openalex.org/I99043593"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.48283063,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5939","last_page":"5946"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.28139999508857727,"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":0.28139999508857727,"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/T12392","display_name":"Sharing Economy and Platforms","score":0.27790001034736633,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.05310000106692314,"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/assortativity","display_name":"Assortativity","score":0.5378999710083008},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4332999885082245},{"id":"https://openalex.org/keywords/transparency","display_name":"Transparency (behavior)","score":0.4239000082015991},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.41110000014305115},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.3772999942302704},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.366100013256073},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.36480000615119934},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.34880000352859497}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7260000109672546},{"id":"https://openalex.org/C89694873","wikidata":"https://www.wikidata.org/wiki/Q4810299","display_name":"Assortativity","level":3,"score":0.5378999710083008},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4332999885082245},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42969998717308044},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.4239000082015991},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.41110000014305115},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4049000144004822},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3903999924659729},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.3772999942302704},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.366100013256073},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.36480000615119934},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.35740000009536743},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.321399986743927},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.31679999828338623},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30720001459121704},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.29409998655319214},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.26750001311302185},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.25940001010894775},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746252.3761552","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746252.3761552","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3746252.3761552","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746252.3761552","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1493122757","https://openalex.org/W1541504294","https://openalex.org/W2017085528","https://openalex.org/W2058336014","https://openalex.org/W2073483673","https://openalex.org/W2085225290","https://openalex.org/W2099932395","https://openalex.org/W2907492528","https://openalex.org/W3152187935","https://openalex.org/W3176130152","https://openalex.org/W4226134687","https://openalex.org/W4386379925","https://openalex.org/W4386858959","https://openalex.org/W4392942767","https://openalex.org/W4400973925","https://openalex.org/W4402516549","https://openalex.org/W4402597304"],"related_works":[],"abstract_inverted_index":{"Dynamic":[0],"pricing":[1,31,160],"on":[2,124],"two-sided":[3],"platforms":[4],"such":[5],"as":[6],"Airbnb":[7,126],"presents":[8],"complex":[9],"challenges":[10],"due":[11],"to":[12,42,59],"the":[13,44,87,146],"heterogeneity":[14],"of":[15,46,148],"listings,":[16],"user":[17],"behaviours,":[18],"and":[19,29,39,51,89,97,135,140,154],"contextual":[20,107],"variables.":[21],"In":[22],"this":[23],"work,":[24],"we":[25],"propose":[26],"a":[27,79,95],"robust":[28],"interpretable":[30,155],"framework":[32,110],"that":[33,64],"leverages":[34],"Large":[35],"Language":[36],"Models":[37],"(LLMs)":[38],"prompt":[40],"engineering":[41,71],"automate":[43],"generation":[45],"high-level":[47],"meta-features":[48,56],"from":[49],"unstructured":[50],"structured":[52,151],"listing":[53],"data.":[54],"These":[55],"are":[57,65],"designed":[58],"capture":[60],"nuanced":[61],"semantic":[62],"features":[63],"often":[66],"overlooked":[67],"by":[68],"traditional":[69],"feature":[70],"pipelines.":[72],"We":[73],"further":[74],"integrate":[75],"these":[76],"representations":[77],"into":[78],"Transformer-based":[80],"Graph":[81],"Neural":[82],"Network":[83],"(GNN),":[84],"which":[85],"models":[86],"relational":[88],"spatial":[90],"dependencies":[91],"between":[92],"listings":[93],"in":[94,132],"data-driven":[96],"several":[98],"relation-construction":[99],"manner.":[100],"By":[101],"combining":[102],"prompt-driven":[103],"embeddings":[104],"with":[105],"graph-aware":[106],"learning,":[108,153],"our":[109,129],"significantly":[111],"enhances":[112],"price":[113],"recommendation":[114],"accuracy":[115],"while":[116],"offering":[117],"transparency":[118],"through":[119],"assortativity":[120],"analysis.":[121],"Extensive":[122],"experiments":[123],"real-world":[125],"datasets":[127],"demonstrate":[128],"approach's":[130],"performance":[131],"both":[133],"prediction":[134],"unseen":[136],"data":[137],"across":[138],"neighbourhoods":[139],"output":[141],"interpretability.":[142],"This":[143],"work":[144],"highlights":[145],"potential":[147],"unifying":[149],"LLMs,":[150],"graph":[152],"AI":[156],"for":[157],"next-generation":[158],"dynamic":[159],"systems.":[161]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-08T00:00:00"}