{"id":"https://openalex.org/W3201815553","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534384","title":"entity2item: Leveraging Knowledge Graph Embedding for Item Recommendation","display_name":"entity2item: Leveraging Knowledge Graph Embedding for Item Recommendation","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3201815553","doi":"https://doi.org/10.1109/ijcnn52387.2021.9534384","mag":"3201815553"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9534384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5055825962","display_name":"Yuan Yuan","orcid":"https://orcid.org/0000-0001-9678-3369"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuan Yuan","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026602746","display_name":"Yan Tang","orcid":"https://orcid.org/0000-0001-5239-5807"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Tang","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006072880","display_name":"Luomin Du","orcid":"https://orcid.org/0000-0003-1359-5755"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Luoming Du","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100371878","display_name":"Xiaotong Li","orcid":"https://orcid.org/0000-0002-7942-5743"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaotong Li","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5055825962"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":0.5508,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.73357225,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"28","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":0.9993000030517578,"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":0.9922999739646912,"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":0.8569297790527344},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8340794444084167},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.6821424961090088},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6208169460296631},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5519523024559021},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.537859320640564},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.45991554856300354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.370233416557312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36435824632644653},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.23498597741127014}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8569297790527344},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8340794444084167},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.6821424961090088},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6208169460296631},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5519523024559021},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.537859320640564},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.45991554856300354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.370233416557312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36435824632644653},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.23498597741127014}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9534384","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9534384","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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":38,"referenced_works":["https://openalex.org/W2127795553","https://openalex.org/W2184957013","https://openalex.org/W2250342289","https://openalex.org/W2283196293","https://openalex.org/W2402712144","https://openalex.org/W2475334473","https://openalex.org/W2509893387","https://openalex.org/W2743159750","https://openalex.org/W2759136286","https://openalex.org/W2792839191","https://openalex.org/W2796608345","https://openalex.org/W2801992635","https://openalex.org/W2807942528","https://openalex.org/W2895544739","https://openalex.org/W2896962583","https://openalex.org/W2897610297","https://openalex.org/W2899656399","https://openalex.org/W2903212270","https://openalex.org/W2908230750","https://openalex.org/W2911778742","https://openalex.org/W2912351665","https://openalex.org/W2913560138","https://openalex.org/W2948916521","https://openalex.org/W2950133940","https://openalex.org/W2950607928","https://openalex.org/W2955436978","https://openalex.org/W2963869731","https://openalex.org/W2966349618","https://openalex.org/W2984626257","https://openalex.org/W2997897037","https://openalex.org/W3040963377","https://openalex.org/W3084915134","https://openalex.org/W3098087397","https://openalex.org/W3098400049","https://openalex.org/W3106439716","https://openalex.org/W4294170691","https://openalex.org/W6678830454","https://openalex.org/W6752161741"],"related_works":["https://openalex.org/W2604454537","https://openalex.org/W2808284704","https://openalex.org/W2897702399","https://openalex.org/W4206028705","https://openalex.org/W2757431232","https://openalex.org/W2954554213","https://openalex.org/W2251363251","https://openalex.org/W4206547516","https://openalex.org/W4293236197","https://openalex.org/W3036264823"],"abstract_inverted_index":{"Traditional":[0],"recommender":[1,127,167],"systems":[2],"only":[3],"rely":[4],"on":[5,176],"the":[6,32,52,66,93,108,115,124,133,144,149,154,156,180,187],"historical":[7],"interaction":[8],"information":[9,54,67,94],"of":[10,34,42,55,65,91,118,151,158],"users":[11,56,159],"and":[12,30,57,160],"items,":[13],"so":[14,138],"they":[15],"often":[16],"suffer":[17],"from":[18,68,95],"sparsity":[19],"problem.":[20],"Therefore,":[21],"researchers":[22],"utilize":[23],"auxiliary":[24,43],"data":[25,44],"to":[26,61,71,98,113,143,147],"alleviate":[27],"this":[28,83],"problem":[29],"improve":[31],"quality":[33],"recommendation.":[35,101],"Recently":[36],"knowledge":[37,69,96,109,136],"graph":[38,70,110],"as":[39,107],"a":[40,73,88,165],"kind":[41],"has":[45],"attracted":[46],"increasing":[47],"attention,":[48],"which":[49],"can":[50,195],"extract":[51],"semantic":[53],"items.":[58,152],"However,":[59],"how":[60],"make":[62],"full":[63],"use":[64],"build":[72],"better":[74],"recommendation":[75,145],"method":[76,90,185],"is":[77],"still":[78,196],"facing":[79],"numerous":[80],"challenges.":[81],"To":[82],"end,":[84,155],"we":[85,121],"propose":[86],"entity2item,":[87],"novel":[89],"using":[92],"graphs":[97],"assist":[99],"item":[100],"Specifically,":[102],"entity2item":[103],"takes":[104],"translation-based":[105],"model":[106],"embedding":[111],"approach":[112],"learn":[114],"feature":[116],"vectors":[117,140,157],"entities.":[119],"Then":[120],"consider":[122],"that":[123,183],"items":[125,161],"in":[126,135,191],"system":[128,168],"are":[129,141,162],"highly":[130],"correlated":[131],"with":[132],"entities":[134],"graph,":[137],"these":[139],"introduced":[142],"module":[146],"enrich":[148],"expression":[150],"In":[153],"input":[163],"into":[164],"deep":[166],"for":[169],"training.":[170],"Extensive":[171],"experiments":[172],"have":[173],"been":[174],"conducted":[175],"three":[177],"real-world":[178],"datasets,":[179],"results":[181],"demonstrate":[182],"our":[184],"outperforms":[186],"state-of-the-art":[188],"baselines.":[189],"Even":[190],"sparse":[192],"scenarios,":[193],"it":[194],"maintain":[197],"satisfactory":[198],"performance.":[199]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
