{"id":"https://openalex.org/W7157110478","doi":"https://doi.org/10.48550/arxiv.2604.23156","title":"Birds of a Feather Cluster Nearby: a Proximity-Aware Geo-Codebook for Local Service Recommendation","display_name":"Birds of a Feather Cluster Nearby: a Proximity-Aware Geo-Codebook for Local Service Recommendation","publication_year":2026,"publication_date":"2026-04-25","ids":{"openalex":"https://openalex.org/W7157110478","doi":"https://doi.org/10.48550/arxiv.2604.23156"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.23156","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23156","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.23156","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134797341","display_name":"Tian He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Tian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134801158","display_name":"Chen Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134771381","display_name":"Jiawei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Jiawei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134756725","display_name":"Lin Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guo, Lin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134756192","display_name":"Wei Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5002774811","display_name":"Zhuqing Jiang","orcid":"https://orcid.org/0000-0001-6308-5708"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Zhuqing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.5117999911308289,"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":0.5117999911308289,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.10260000079870224,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.08429999649524689,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/service","display_name":"Service (business)","score":0.5839999914169312},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5063999891281128},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5023999810218811},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4422000050544739},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.42329999804496765},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4205000102519989},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4169999957084656},{"id":"https://openalex.org/keywords/geographic-information-system","display_name":"Geographic information system","score":0.4108999967575073}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6711999773979187},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.5839999914169312},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5063999891281128},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5023999810218811},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.47600001096725464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4438999891281128},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4438000023365021},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4422000050544739},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.42329999804496765},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4169999957084656},{"id":"https://openalex.org/C41856607","wikidata":"https://www.wikidata.org/wiki/Q483130","display_name":"Geographic information system","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.38830000162124634},{"id":"https://openalex.org/C123046963","wikidata":"https://www.wikidata.org/wiki/Q22664","display_name":"Geographic coordinate system","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.36629998683929443},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.365200012922287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3544999957084656},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.32030001282691956},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.2915000021457672},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2581000030040741},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.23156","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23156","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.23156","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23156","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.4780226945877075,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Generative":[0],"recommendation":[1,34],"systems":[2],"are":[3,48],"increasingly":[4],"adopted":[5],"in":[6,25,45,90,105,149],"local":[7,68,156],"service":[8,157],"platforms,":[9],"where":[10],"semantic":[11,26,38,97],"relevance":[12],"alone":[13],"is":[14],"insufficient":[15],"without":[16,109],"strict":[17],"geographic":[18,41,84,111,139],"feasibility.":[19],"A":[20],"key":[21],"technical":[22],"challenge":[23],"lies":[24],"ID":[27],"(SID)":[28],"tokenization,":[29],"which":[30],"directly":[31],"impacts":[32],"the":[33,91,137],"performance.":[35],"However,":[36],"existing":[37],"codebooks":[39],"neglect":[40],"constraints,":[42],"often":[43],"resulting":[44],"recommendations":[46],"that":[47,82,127],"semantically":[49],"relevant":[50],"yet":[51],"geographically":[52],"unreachable.":[53],"To":[54],"address":[55],"this":[56],"limitation,":[57],"we":[58],"propose":[59],"Pro-GEO,":[60],"a":[61,66,77,106,114,122,146],"Proximity-aware":[62],"GEO-codebook.":[63],"Pro-GEO":[64,128,135],"establishes":[65],"geo-centroid":[67],"coordinate":[69],"system":[70],"to":[71,101,113],"capture":[72],"intra-cluster":[73],"spatial":[74,99],"relationships":[75],"and":[76,98,144],"geo-rotary":[78],"position":[79],"encoding":[80],"mechanism":[81],"models":[83],"proximity":[85],"as":[86],"orthogonal":[87],"rotational":[88],"transformations":[89],"high-dimensional":[92],"embedding.":[93],"This":[94],"design":[95],"enables":[96],"signals":[100],"be":[102],"jointly":[103],"modeled":[104],"balanced":[107],"manner,":[108],"reducing":[110],"information":[112],"weak":[115],"auxiliary":[116],"feature.":[117],"Extensive":[118],"experiments":[119],"conducted":[120],"on":[121],"large-scale":[123],"industrial":[124],"dataset":[125],"reveal":[126],"significantly":[129],"outperforms":[130],"state-of-the-art":[131],"methods.":[132],"In":[133],"particular,":[134],"reduces":[136],"average":[138],"clustering":[140],"distance":[141],"by":[142],"45.60%":[143],"achieves":[145],"1.87%":[147],"improvement":[148],"Hit@50,":[150],"highlighting":[151],"its":[152],"effectiveness":[153],"for":[154],"real-world":[155],"recommendation.":[158]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-29T00:00:00"}