{"id":"https://openalex.org/W7147646394","doi":"https://doi.org/10.1109/cw68232.2025.00062","title":"Semantic Integrity Preserving Recommendation Framework with Large Language Models","display_name":"Semantic Integrity Preserving Recommendation Framework with Large Language Models","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W7147646394","doi":"https://doi.org/10.1109/cw68232.2025.00062"},"language":null,"primary_location":{"id":"doi:10.1109/cw68232.2025.00062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cw68232.2025.00062","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Cyberworlds (CW\uff09","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":"https://openalex.org/A5132563017","display_name":"Rongbing Niu","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongbing Niu","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,Nanjing,China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132614238","display_name":"Yunfeng Fan","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunfeng Fan","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,Nanjing,China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021276803","display_name":"HaiBo Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haibo Ye","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics,Nanjing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics,Nanjing,China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9842412"],"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":"374","last_page":"381"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.6044999957084656,"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":0.6044999957084656,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.10289999842643738,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.07890000194311142,"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/leverage","display_name":"Leverage (statistics)","score":0.6784999966621399},{"id":"https://openalex.org/keywords/bridging","display_name":"Bridging (networking)","score":0.5160999894142151},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5116000175476074},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.4781000018119812},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.45559999346733093},{"id":"https://openalex.org/keywords/semantic-matching","display_name":"Semantic matching","score":0.4140999913215637},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.4099000096321106},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3831000030040741},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.3734999895095825},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3659000098705292}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8540999889373779},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6784999966621399},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5974000096321106},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5378000140190125},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.5160999894142151},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5116000175476074},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.4781000018119812},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.45559999346733093},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.4140999913215637},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.4099000096321106},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3790000081062317},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3734999895095825},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3617999851703644},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.34549999237060547},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.34529998898506165},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.326200008392334},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31790000200271606},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.30889999866485596},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.30799999833106995},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2773999869823456},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C2983448237","wikidata":"https://www.wikidata.org/wiki/Q1078276","display_name":"Language understanding","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.25609999895095825},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.25459998846054077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cw68232.2025.00062","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cw68232.2025.00062","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Cyberworlds (CW\uff09","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.43236044049263}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2171960770","https://openalex.org/W2294798173","https://openalex.org/W2339258924","https://openalex.org/W2605350416","https://openalex.org/W2945827670","https://openalex.org/W2984100107","https://openalex.org/W2998431760","https://openalex.org/W3045200674","https://openalex.org/W3097300053","https://openalex.org/W4284666445","https://openalex.org/W4288083766","https://openalex.org/W4296591867","https://openalex.org/W4327525152","https://openalex.org/W4386728933","https://openalex.org/W4386729952","https://openalex.org/W4392367398","https://openalex.org/W4392384371","https://openalex.org/W4396758712","https://openalex.org/W4396843692"],"related_works":[],"abstract_inverted_index":{"Recommendation":[0,80],"systems":[1],"based":[2,82],"on":[3,83],"deep":[4],"learning":[5,147],"and":[6,58,65,85,104,131,157],"graph":[7],"neural":[8],"networks":[9],"have":[10],"effectively":[11,135],"captured":[12],"complex":[13],"user-item":[14],"relationships":[15],"but":[16],"struggle":[17],"to":[18,30,92,121],"fully":[19],"leverage":[20],"textual":[21],"data":[22,64],"for":[23],"personalized":[24],"recommendations.":[25],"This":[26],"is":[27],"primarily":[28],"due":[29],"three":[31],"key":[32],"challenges:":[33],"(1)":[34],"shallow":[35],"semantic":[36,43],"integration":[37],"in":[38,62,101],"language":[39,50],"model":[40,51],"representations,":[41],"(2)":[42],"degradation":[44],"during":[45],"the":[46,123,151],"fusion":[47,113],"of":[48],"large":[49],"(LLM)":[52],"embeddings":[53,130],"with":[54,145],"collaborative":[55,132],"filtering":[56,133],"signals,":[57,134],"(3)":[59],"scalability":[60],"bottlenecks":[61],"sparse":[63],"large-scale":[66],"interaction":[67,158],"scenarios.":[68],"To":[69],"address":[70],"these":[71],"challenges,":[72],"we":[73],"propose":[74],"SIP-Rec,":[75],"a":[76,117],"Semantic":[77],"Integrity":[78],"Preserving":[79],"Framework":[81],"LLM":[84,91,129],"contrastive":[86,146],"learning.":[87],"First,":[88],"SIP-Rec":[89,149],"utilizes":[90],"generate":[93],"semantically":[94,154],"rich":[95,155],"profiles,":[96],"accurately":[97],"capturing":[98],"fine-grained":[99],"differences":[100],"user":[102],"preferences":[103],"item":[105],"characteristics.":[106],"Second,":[107],"it":[108],"introduces":[109],"an":[110],"innovative":[111],"cross-modal":[112],"mechanism":[114],"that":[115],"employs":[116],"dynamic":[118],"alignment":[119],"strategy":[120],"bridge":[122],"representation":[124],"space":[125],"gap":[126],"between":[127,153],"high-dimensional":[128],"mitigating":[136],"contextual":[137],"information":[138],"loss.":[139],"Finally,":[140],"by":[141],"integrating":[142],"knowledge":[143],"distillation":[144],"objectives,":[148],"optimizes":[150],"consistency":[152],"representations":[156],"patterns.":[159]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-04-02T00:00:00"}