{"id":"https://openalex.org/W3104166230","doi":"https://doi.org/10.1109/tkde.2020.3037029","title":"Generating Knowledge-Based Attentive User Representations for Sparse Interaction Recommendation","display_name":"Generating Knowledge-Based Attentive User Representations for Sparse Interaction Recommendation","publication_year":2020,"publication_date":"2020-11-10","ids":{"openalex":"https://openalex.org/W3104166230","doi":"https://doi.org/10.1109/tkde.2020.3037029","mag":"3104166230"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2020.3037029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3037029","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5072181882","display_name":"Deqing Yang","orcid":"https://orcid.org/0000-0002-1390-3861"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deqing Yang","raw_affiliation_strings":["School of Data Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-1390-3861","affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101932919","display_name":"Chenlu Shen","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenlu Shen","raw_affiliation_strings":["School of Data Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6676-1975","affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102974205","display_name":"Baichuan Liu","orcid":"https://orcid.org/0000-0003-0308-9007"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baichuan Liu","raw_affiliation_strings":["School of Data Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077953276","display_name":"Lyuxin Xue","orcid":"https://orcid.org/0000-0001-9433-9176"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lyuxin Xue","raw_affiliation_strings":["School of Data Science, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9433-9176","affiliations":[{"raw_affiliation_string":"School of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090455375","display_name":"Yanghua Xiao","orcid":"https://orcid.org/0000-0001-8403-9591"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanghua Xiao","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China","Shanghai Institute of Intelligent, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Shanghai Institute of Intelligent, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":1.3606,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.8681853,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"34","issue":"9","first_page":"4270","last_page":"4284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9958999752998352,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9714999794960022,"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":0.8402825593948364},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7985236048698425},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7414565086364746},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.7005832195281982},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5625593066215515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49887776374816895},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4782765805721283},{"id":"https://openalex.org/keywords/user-modeling","display_name":"User modeling","score":0.47669193148612976},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4398486316204071},{"id":"https://openalex.org/keywords/cold-start","display_name":"Cold start (automotive)","score":0.41251468658447266},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3383330702781677},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.32786983251571655},{"id":"https://openalex.org/keywords/user-interface","display_name":"User interface","score":0.2312498390674591}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8402825593948364},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7985236048698425},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7414565086364746},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.7005832195281982},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5625593066215515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49887776374816895},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4782765805721283},{"id":"https://openalex.org/C67712803","wikidata":"https://www.wikidata.org/wiki/Q7901853","display_name":"User modeling","level":3,"score":0.47669193148612976},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4398486316204071},{"id":"https://openalex.org/C2778956030","wikidata":"https://www.wikidata.org/wiki/Q5142477","display_name":"Cold start (automotive)","level":2,"score":0.41251468658447266},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3383330702781677},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32786983251571655},{"id":"https://openalex.org/C89505385","wikidata":"https://www.wikidata.org/wiki/Q47146","display_name":"User interface","level":2,"score":0.2312498390674591},{"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2020.3037029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2020.3037029","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1994389483","https://openalex.org/W2000822082","https://openalex.org/W2010187764","https://openalex.org/W2049455633","https://openalex.org/W2054141820","https://openalex.org/W2061503185","https://openalex.org/W2070493638","https://openalex.org/W2094728533","https://openalex.org/W2108920354","https://openalex.org/W2138605095","https://openalex.org/W2146502635","https://openalex.org/W2150886314","https://openalex.org/W2153225416","https://openalex.org/W2159155347","https://openalex.org/W2213191543","https://openalex.org/W2295739661","https://openalex.org/W2475334473","https://openalex.org/W2509893387","https://openalex.org/W2604662567","https://openalex.org/W2605350416","https://openalex.org/W2620787630","https://openalex.org/W2723293840","https://openalex.org/W2741249238","https://openalex.org/W2743159750","https://openalex.org/W2750004028","https://openalex.org/W2783272285","https://openalex.org/W2788663865","https://openalex.org/W2798385737","https://openalex.org/W2801992635","https://openalex.org/W2802187397","https://openalex.org/W2884134047","https://openalex.org/W2907349915","https://openalex.org/W2911778742","https://openalex.org/W2913560138","https://openalex.org/W2945623882","https://openalex.org/W2963323306","https://openalex.org/W2963869731","https://openalex.org/W2964052347","https://openalex.org/W2964182926","https://openalex.org/W2987684747","https://openalex.org/W3091993229","https://openalex.org/W3101830194","https://openalex.org/W3106439716","https://openalex.org/W4234189512","https://openalex.org/W4299286960","https://openalex.org/W4385245566","https://openalex.org/W6601546654","https://openalex.org/W6636888537","https://openalex.org/W6680830989","https://openalex.org/W6681435938","https://openalex.org/W6682137061","https://openalex.org/W6682889407","https://openalex.org/W6692935382","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W1484355083","https://openalex.org/W2772628444","https://openalex.org/W4220714703","https://openalex.org/W2170391450","https://openalex.org/W2098758514","https://openalex.org/W3008845055","https://openalex.org/W2041004656","https://openalex.org/W135044020","https://openalex.org/W2358418295","https://openalex.org/W2735929803"],"abstract_inverted_index":{"Deep":[0],"neural":[1,146],"networks":[2],"(DNNs)":[3],"have":[4],"been":[5],"widely":[6],"imported":[7],"into":[8],"collaborative-filtering":[9],"(CF)":[10],"based":[11,44],"recommender":[12],"systems":[13],"and":[14,38,85,99,176],"yielded":[15],"remarkable":[16,182],"superiority":[17,183],"over":[18,184],"traditional":[19],"recommendation":[20,58,162,188],"models.":[21,189],"However,":[22],"most":[23],"deep":[24,56,187],"CF-based":[25],"models":[26],"perform":[27],"weakly":[28],"when":[29],"observed":[30,46],"user-item":[31,74],"interactions":[32],"are":[33,41,101,129],"sparse":[34,72],"since":[35],"user":[36,108,127,139,154,158],"preferences":[37],"item":[39],"characteristics":[40],"inferred":[42],"mainly":[43],"on":[45],"(historical)":[47],"interactions.":[48],"To":[49],"address":[50],"this":[51,61],"problem,":[52],"we":[53,76,110,142],"propose":[54],"a":[55,112,144],"knowledge-enhanced":[57],"model":[59],"in":[60,68,153],"paper.":[62],"Specifically,":[63],"to":[64,104,134,148],"augment":[65],"user/item":[66],"representations":[67,128,155],"the":[69,79,136,150,185],"scenario":[70],"of":[71,88,97,138],"historical":[73,123],"interactions,":[75],"first":[77],"incorporate":[78],"knowledge":[80,83],"from":[81,93],"open":[82],"graphs":[84],"personal":[86],"information":[87],"users":[89,98],"as":[90],"side":[91],"information,":[92],"which":[94,160],"sufficient":[95],"features":[96,152],"items":[100,119],"extracted.":[102],"Second,":[103],"well":[105],"capture":[106,135],"shifted":[107],"preferences,":[109],"leverage":[111],"memory":[113],"component":[114],"constituted":[115],"by":[116,131],"recently":[117],"interacted":[118],"rather":[120],"than":[121],"all":[122],"ones.":[124],"Third,":[125],"attentive":[126],"generated":[130],"attention":[132],"mechanism":[133],"diversity":[137],"preferences.":[140],"Furthermore,":[141],"build":[143],"convolutional":[145],"network":[147],"pool":[149],"latent":[151],"for":[156],"better":[157],"modeling,":[159],"enhances":[161],"performance":[163],"further.":[164],"Our":[165],"extensive":[166],"experiments":[167],"conducted":[168],"against":[169],"two":[170],"real-world":[171],"datasets,":[172],"i.e.,":[173],"Douban":[174],"movie":[175],"NetEase":[177],"music,":[178],"demonstrate":[179],"our":[180],"model\u2019s":[181],"state-of-the-art":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}