{"id":"https://openalex.org/W7204145577","doi":"https://doi.org/10.48550/arxiv.2608.21243","title":"Adapting Knowledge Graphs for Behavior Denoising in Sequential Recommendation","display_name":"Adapting Knowledge Graphs for Behavior Denoising in Sequential Recommendation","publication_year":2026,"publication_date":"2026-08-21","ids":{"openalex":"https://openalex.org/W7204145577","doi":"https://doi.org/10.48550/arxiv.2608.21243"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2608.21243","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.21243","pdf_url":"https://arxiv.org/pdf/2608.21243","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2608.21243","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5147949842","display_name":"Zichun Jin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin, Zichun","raw_affiliation_strings":["Northeastern University , Shenyang , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University , Shenyang , China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124436675","display_name":"Zihan Zhou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhou, Zihan","raw_affiliation_strings":["Northeastern University , Shenyang , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University , Shenyang , China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124238884","display_name":"Yinan Liu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liu, Yinan","raw_affiliation_strings":["Northeastern University , Shenyang , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University , Shenyang , China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5147983281","display_name":"Bin Wang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wang, Bin","raw_affiliation_strings":["Northeastern University , Shenyang , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University , Shenyang , China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125772783","display_name":"Xiaochun Yang","orcid":"https://orcid.org/0000-0002-6184-4771","observed_orcids":["https://orcid.org/0000-0002-6184-4771"]},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang, Xiaochun","raw_affiliation_strings":["Northeastern University , Shenyang , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Northeastern University , Shenyang , China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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":1.0,"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":1.0,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.0,"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":0.0,"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/sequential-recommendation","display_name":"sequential recommendation","score":0.781000018119812},{"id":"https://openalex.org/keywords/knowledge-graphs","display_name":"knowledge graphs","score":0.9869999885559082},{"id":"https://openalex.org/keywords/retention-coefficient","display_name":"retention coefficient","score":0.6830000281333923},{"id":"https://openalex.org/keywords/loss-reweighting","display_name":"loss reweighting","score":0.6499999761581421}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7347000241279602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.560699999332428},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.546999990940094},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5333999991416931},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5198000073432922},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5059000253677368},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4943000078201294},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.45339998602867126},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3587999939918518},{"id":"https://openalex.org/C177877439","wikidata":"https://www.wikidata.org/wiki/Q7604413","display_name":"Statistical relational learning","level":3,"score":0.3402000069618225},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33660000562667847},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33160001039505005},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.29010000824928284},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.26739999651908875},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.25769999623298645}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2608.21243","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.21243","pdf_url":"https://arxiv.org/pdf/2608.21243","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2608.21243","doi":"https://doi.org/10.48550/arxiv.2608.21243","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2608.21243","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2608.21243","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2608.21243","pdf_url":"https://arxiv.org/pdf/2608.21243","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7204145577.pdf","grobid_xml":"https://content.openalex.org/works/W7204145577.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4387757606","https://openalex.org/W3199258356","https://openalex.org/W4392384830","https://openalex.org/W4403147873","https://openalex.org/W4288472167","https://openalex.org/W4405673630","https://openalex.org/W4412633719","https://openalex.org/W4385778235","https://openalex.org/W4386938119","https://openalex.org/W4285211792"],"abstract_inverted_index":{"Sequential":[0],"recommendation":[1,104],"predicts":[2],"the":[3,103,109,175],"next":[4],"item":[5,68],"from":[6,48,57],"a":[7,129,171,191],"user's":[8],"interaction":[9,14,137],"history,":[10],"but":[11,67],"not":[12],"every":[13],"is":[15,183],"equally":[16],"informative.":[17],"Real":[18],"logs":[19],"combine":[20],"persistent":[21],"preferences":[22],"with":[23,112,138,190],"temporary":[24],"needs,":[25],"exploration,":[26],"and":[27,74,81,124,157,170,179,195],"incidental":[28],"behavior,":[29],"so":[30,174],"some":[31],"interactions":[32,46,169],"can":[33,78],"distort":[34],"history":[35],"representations":[36,101,156],"or":[37,51],"provide":[38],"unreliable":[39],"supervision.":[40],"Existing":[41],"denoising":[42],"methods":[43],"judge":[44],"such":[45],"mainly":[47],"co-occurrence,":[49],"order,":[50],"model":[52],"predictions,":[53],"without":[54,98],"explicit":[55],"evidence":[56,93],"relations":[58],"between":[59],"items.":[60],"Knowledge":[61],"graphs":[62],"(KGs)":[63],"offer":[64],"this":[65],"evidence,":[66],"popularity,":[69],"graph":[70,100],"degree,":[71],"uneven":[72],"coverage,":[73],"widely":[75],"shared":[76],"entities":[77],"inflate":[79],"connectivity":[80],"bias":[82],"reliability":[83],"estimates.":[84],"Here":[85],"we":[86],"present":[87],"AdaptedKG,":[88],"which":[89],"derives":[90],"calibrated":[91],"KG":[92,131,181],"for":[94],"each":[95,136],"training":[96,168],"example":[97],"adding":[99],"to":[102,116,127,143],"model.":[105],"It":[106,133],"first":[107],"compares":[108,135],"observed":[110],"context":[111],"structurally":[113,139],"matched":[114,140],"alternatives":[115],"identify":[117],"relational":[118],"paths":[119],"that":[120,148],"are":[121,164],"unusually":[122],"prominent":[123],"uses":[125],"them":[126],"build":[128],"local":[130],"view.":[132,149],"then":[134],"reference":[141],"items":[142],"calibrate":[144],"its":[145],"support":[146],"within":[147],"The":[150],"resulting":[151],"retention":[152],"coefficients":[153],"gate":[154],"historical":[155],"reweight":[158],"target":[159],"losses.":[160],"All":[161],"sample-specific":[162],"scores":[163],"computed":[165],"offline":[166],"using":[167],"fixed":[172],"KG,":[173],"backbone":[176],"remains":[177],"unchanged":[178],"no":[180],"access":[182],"required":[184],"at":[185],"inference.":[186],"Experiments":[187],"show":[188],"gains":[189],"standard":[192],"sequential":[193,198],"recommender":[194],"multiple":[196],"behavior-denoising":[197],"recommenders.":[199]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-08-25T00:00:00"}