{"id":"https://openalex.org/W7115186840","doi":"https://doi.org/10.1109/ictai66417.2025.00044","title":"Dual-Channel Disentangled Contrastive Learning with Adaptive Spatio-Temporal Encoding for POI Recommendation","display_name":"Dual-Channel Disentangled Contrastive Learning with Adaptive Spatio-Temporal Encoding for POI Recommendation","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W7115186840","doi":"https://doi.org/10.1109/ictai66417.2025.00044"},"language":null,"primary_location":{"id":"doi:10.1109/ictai66417.2025.00044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictai66417.2025.00044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI)","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":null,"display_name":"Yongxuan Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxuan Feng","raw_affiliation_strings":["East China University of Science and Technology,School of Information Science and Engineering,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology,School of Information Science and Engineering,Shanghai,China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Binlu Yan","orcid":null},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Binlu Yan","raw_affiliation_strings":["East China University of Science and Technology,School of Resources and Environmental Engineering,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology,School of Resources and Environmental Engineering,Shanghai,China","institution_ids":["https://openalex.org/I143593769"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhanquan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I143593769","display_name":"East China University of Science and Technology","ror":"https://ror.org/01vyrm377","country_code":"CN","type":"education","lineage":["https://openalex.org/I143593769"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanquan Wang","raw_affiliation_strings":["East China University of Science and Technology,School of Information Science and Engineering,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"East China University of Science and Technology,School of Information Science and Engineering,Shanghai,China","institution_ids":["https://openalex.org/I143593769"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I143593769"],"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":"284","last_page":"291"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.953000009059906,"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":0.953000009059906,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.006500000134110451,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.006200000178068876,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.6690999865531921},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5687999725341797},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5375999808311462},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45500001311302185},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.3901999890804291},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.38929998874664307},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3815000057220459},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.3776000142097473}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8648999929428101},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.6690999865531921},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6399999856948853},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5687999725341797},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5375999808311462},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45829999446868896},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45500001311302185},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43070000410079956},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3901999890804291},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.38929998874664307},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.3776000142097473},{"id":"https://openalex.org/C142172996","wikidata":"https://www.wikidata.org/wiki/Q221284","display_name":"Conformity","level":2,"score":0.37049999833106995},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.320499986410141},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2847999930381775},{"id":"https://openalex.org/C125014702","wikidata":"https://www.wikidata.org/wiki/Q4680749","display_name":"Adaptive learning","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.27300000190734863},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2583000063896179}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictai66417.2025.00044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictai66417.2025.00044","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2017921654","https://openalex.org/W2071702404","https://openalex.org/W2110953678","https://openalex.org/W2116341502","https://openalex.org/W2539781657","https://openalex.org/W2770823020","https://openalex.org/W2788114581","https://openalex.org/W2790294742","https://openalex.org/W2801624499","https://openalex.org/W2965286893","https://openalex.org/W2987050385","https://openalex.org/W2998167534","https://openalex.org/W3034646226","https://openalex.org/W3102247173","https://openalex.org/W3128267727","https://openalex.org/W3129017148","https://openalex.org/W3129186620","https://openalex.org/W3156939347","https://openalex.org/W3189845972","https://openalex.org/W4205551258","https://openalex.org/W4284668299","https://openalex.org/W4297963447","https://openalex.org/W4306317228","https://openalex.org/W4383503819","https://openalex.org/W4385245566","https://openalex.org/W4387322836","https://openalex.org/W4387846632","https://openalex.org/W4391528991","https://openalex.org/W4393156329","https://openalex.org/W4397012985","https://openalex.org/W4399617935","https://openalex.org/W4400386332","https://openalex.org/W4402157441","https://openalex.org/W4408441365"],"related_works":[],"abstract_inverted_index":{"In":[0],"point-of-interest":[1],"(POI)":[2],"recommendation,":[3],"users'":[4],"behaviors":[5,96],"evolve":[6],"across":[7],"contexts,":[8],"making":[9],"it":[10],"hard":[11],"for":[12],"static":[13],"models":[14,65],"to":[15,27,92],"capture":[16],"heterogeneous":[17],"patterns.":[18],"Additionally,":[19],"group":[20,95],"conformity":[21],"introduces":[22],"popularity":[23,107],"bias,":[24],"causing":[25],"systems":[26],"over-recommend":[28],"frequent":[29],"POIs":[30],"while":[31],"overlooking":[32],"long-tail":[33,102],"interests.":[34],"To":[35],"address":[36],"these":[37],"issues,":[38],"we":[39,56],"propose":[40],"DCDST,":[41],"a":[42,58,72],"novel":[43],"framework":[44],"that":[45,63,115],"combines":[46],"dual-channel":[47,73],"disentangled":[48],"contrastive":[49,74],"learning":[50,75],"with":[51],"adaptive":[52],"spatio-temporal":[53,59],"encoding.":[54],"Specifically,":[55],"introduce":[57],"bias-aware":[60],"self-attention":[61],"mechanism":[62],"dynamically":[64],"contextual":[66],"dependencies":[67],"within":[68],"user":[69],"trajectories.":[70],"Simultaneously,":[71],"module":[76],"generates":[77],"adversarial":[78],"views":[79],"through":[80],"group-level":[81],"augmentation":[82],"and":[83,105,124],"individual-specific":[84],"perturbation.":[85],"A":[86],"conformity-aware":[87],"loss":[88],"function":[89],"is":[90,129],"employed":[91],"disentangle":[93],"shared":[94],"from":[97],"personalized":[98],"preferences,":[99],"enabling":[100],"better":[101],"interest":[103],"modeling":[104],"mitigating":[106],"bias.":[108],"Experiments":[109],"on":[110],"three":[111],"real-world":[112],"datasets":[113],"demonstrate":[114],"DCDST":[116],"consistently":[117],"outperforms":[118],"state-of-the-art":[119],"methods":[120],"in":[121],"both":[122],"accuracy":[123],"recommendation":[125],"diversity.":[126],"Our":[127],"code":[128],"available":[130],"at":[131],"https://github.com/yx-Feng/DCDST.":[132]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-12-15T00:00:00"}