{"id":"https://openalex.org/W4312290028","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892593","title":"A Knowledge Graph Recommendation Model via High-order Feature Interaction and Intent Decomposition","display_name":"A Knowledge Graph Recommendation Model via High-order Feature Interaction and Intent Decomposition","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312290028","doi":"https://doi.org/10.1109/ijcnn55064.2022.9892593"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9892593","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892593","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"article","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/A5103211587","display_name":"Ruoyi Zhang","orcid":"https://orcid.org/0000-0002-7941-2969"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruoyi Zhang","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University,Lanzhou,China","College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University,Lanzhou,China","institution_ids":["https://openalex.org/I68986083"]},{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053794277","display_name":"Huifang Ma","orcid":"https://orcid.org/0000-0002-5104-8982"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]},{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huifang Ma","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University,Lanzhou,China","College of Computer Science and Information Technology, Guangxi Normal University, Guilin, China","College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University,Lanzhou,China","institution_ids":["https://openalex.org/I68986083"]},{"raw_affiliation_string":"College of Computer Science and Information Technology, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]},{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100349222","display_name":"Qingfeng Li","orcid":"https://orcid.org/0000-0002-3603-7580"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingfeng Li","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University,Lanzhou,China","College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University,Lanzhou,China","institution_ids":["https://openalex.org/I68986083"]},{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China","institution_ids":["https://openalex.org/I68986083"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701695","display_name":"Zhixin Li","orcid":"https://orcid.org/0000-0002-5313-6134"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixin Li","raw_affiliation_strings":["College of Computer Science and Information Technology, Guangxi Normal University,Guilin,China","College of Computer Science and Information Technology, Guangxi Normal University, Guilin, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Information Technology, Guangxi Normal University,Guilin,China","institution_ids":["https://openalex.org/I29739308"]},{"raw_affiliation_string":"College of Computer Science and Information Technology, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101678590","display_name":"Yike Wang","orcid":"https://orcid.org/0009-0005-9765-8742"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yike Wang","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University,Lanzhou,China","College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University,Lanzhou,China","institution_ids":["https://openalex.org/I68986083"]},{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China","institution_ids":["https://openalex.org/I68986083"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103211587"],"corresponding_institution_ids":["https://openalex.org/I68986083"],"apc_list":null,"apc_paid":null,"fwci":0.8731,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.76595128,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9995999932289124,"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/T10028","display_name":"Topic Modeling","score":0.9958999752998352,"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/computer-science","display_name":"Computer science","score":0.8114957809448242},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6165255308151245},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.5732522010803223},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5436335206031799},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5337062478065491},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.5289801359176636},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5168388485908508},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.493375688791275},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48132097721099854},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46685200929641724},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4339437484741211},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4186834692955017},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38189560174942017},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3223280906677246},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2526392936706543}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8114957809448242},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6165255308151245},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.5732522010803223},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5436335206031799},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5337062478065491},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.5289801359176636},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5168388485908508},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.493375688791275},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48132097721099854},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46685200929641724},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4339437484741211},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4186834692955017},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38189560174942017},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3223280906677246},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2526392936706543},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9892593","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9892593","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17"}],"awards":[{"id":"https://openalex.org/G6757566773","display_name":null,"funder_award_id":"61762078,61363058,U1811264,61966004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W2010187764","https://openalex.org/W2095705004","https://openalex.org/W2509893387","https://openalex.org/W2783272285","https://openalex.org/W2792839191","https://openalex.org/W2887997457","https://openalex.org/W2913560138","https://openalex.org/W2945623882","https://openalex.org/W2963911286","https://openalex.org/W3024534448","https://openalex.org/W3034364571","https://openalex.org/W3093570486","https://openalex.org/W3098087397","https://openalex.org/W3106439716","https://openalex.org/W3154920485","https://openalex.org/W3176365208","https://openalex.org/W3193441787","https://openalex.org/W3210317057","https://openalex.org/W3210910782","https://openalex.org/W3210938103","https://openalex.org/W4200554615","https://openalex.org/W4206736823","https://openalex.org/W4226157887","https://openalex.org/W4226416726","https://openalex.org/W4297733535","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6674330103","https://openalex.org/W6754278344"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W1484355083","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W2098758514","https://openalex.org/W3008845055","https://openalex.org/W2170391450","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622"],"abstract_inverted_index":{"Knowledge":[0,78],"Graph(KG)":[1],"contains":[2],"structured":[3],"attribute":[4],"information":[5],"which":[6,89],"has":[7],"been":[8],"widely":[9],"utilized":[10],"for":[11],"recommendations,":[12],"as":[13,15,36],"well":[14],"can":[16,43],"effectively":[17],"tackle":[18],"the":[19,92,110,116,120,125,152,155],"sparsity":[20],"and":[21,60,63,86,96,137],"cold":[22],"start":[23],"problems":[24],"of":[25,154],"collaborative":[26],"filtering.":[27],"In":[28,69],"recent":[29],"years,":[30],"Graph":[31,79],"Neural":[32],"Networks":[33],"(GNNs)":[34],"serve":[35],"a":[37,74],"novel":[38],"deep":[39],"learning":[40],"technique":[41],"that":[42],"significantly":[44],"enhance":[45],"recommendation":[46,80],"performance.":[47],"Unfortunately,":[48],"existing":[49],"KG-based":[50,100],"GNN":[51,101],"models":[52,91],"are":[53,107,140],"coarse-grained":[54],"ignoring":[55],"i)effective":[56],"high-order":[57,83,104],"feature":[58,84,94,105],"interaction":[59,95],"fusion":[61],"mechanism":[62],"ii)interpretable":[64],"user":[65,126,135],"latent":[66],"intent":[67,87,97,122],"decomposition.":[68],"this":[70],"paper,":[71],"we":[72],"propose":[73],"new":[75],"method":[76],"named":[77],"model":[81],"via":[82,109],"Interaction":[85],"Decomposition(KGID),":[88],"explicitly":[90],"fine-grained":[93],"factors":[98],"in":[99],"recommendation.":[102],"Initially,":[103],"interactions":[106],"captured":[108],"two-granularity":[111],"convolutional":[112],"neural":[113],"networks":[114],"on":[115,146],"item":[117,138],"side.":[118],"Next,":[119],"implicit":[121],"factor":[123],"behind":[124],"decisions":[127],"is":[128],"modeled":[129],"by":[130],"two-level":[131],"attention":[132],"mechanisms.":[133],"Ultimately,":[134],"representations":[136,139],"augmented":[141],"simultaneously.":[142],"We":[143],"conduct":[144],"experiments":[145],"three":[147],"benchmark":[148],"datasets":[149],"to":[150,157],"elucidate":[151],"superiority":[153],"KGID":[156],"state-of-the-art":[158],"baselines.":[159]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}