{"id":"https://openalex.org/W3093965624","doi":"https://doi.org/10.1145/3340531.3412069","title":"Dual Autoencoder Network with Swap Reconstruction for Cold-Start Recommendation","display_name":"Dual Autoencoder Network with Swap Reconstruction for Cold-Start Recommendation","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3093965624","doi":"https://doi.org/10.1145/3340531.3412069","mag":"3093965624"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3412069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3412069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management","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/A5100349945","display_name":"Bei Wang","orcid":"https://orcid.org/0000-0002-3602-2557"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bei Wang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091646587","display_name":"Chenrui Zhang","orcid":"https://orcid.org/0000-0001-6788-0004"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenrui Zhang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069635843","display_name":"Hao Zhang","orcid":"https://orcid.org/0000-0001-5598-9926"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhang","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101587591","display_name":"Xiaoqing Lyu","orcid":"https://orcid.org/0000-0003-2354-7749"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqing Lyu","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103175239","display_name":"Zhi Tang","orcid":"https://orcid.org/0000-0002-6021-8357"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Tang","raw_affiliation_strings":["Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100349945"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":1.6014,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.88096278,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2249","last_page":"2252"},"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":0.9966999888420105,"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":0.9571999907493591,"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/autoencoder","display_name":"Autoencoder","score":0.8479532599449158},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8094123601913452},{"id":"https://openalex.org/keywords/cold-start","display_name":"Cold start (automotive)","score":0.7459664344787598},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5929996967315674},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.5763107538223267},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5719349384307861},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5591567754745483},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5307286381721497},{"id":"https://openalex.org/keywords/swap","display_name":"Swap (finance)","score":0.5275359153747559},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5031809210777283},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.4902418255805969},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.48540839552879333},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4603895843029022},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38406962156295776},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.38230469822883606},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37302297353744507},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3708134889602661}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8479532599449158},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8094123601913452},{"id":"https://openalex.org/C2778956030","wikidata":"https://www.wikidata.org/wiki/Q5142477","display_name":"Cold start (automotive)","level":2,"score":0.7459664344787598},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5929996967315674},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.5763107538223267},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5719349384307861},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5591567754745483},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5307286381721497},{"id":"https://openalex.org/C99821215","wikidata":"https://www.wikidata.org/wiki/Q1136583","display_name":"Swap (finance)","level":2,"score":0.5275359153747559},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5031809210777283},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.4902418255805969},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.48540839552879333},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4603895843029022},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38406962156295776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38230469822883606},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37302297353744507},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3708134889602661},{"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/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3340531.3412069","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3412069","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management","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":12,"referenced_works":["https://openalex.org/W2400248106","https://openalex.org/W2519887557","https://openalex.org/W2604433096","https://openalex.org/W2740605635","https://openalex.org/W2782731323","https://openalex.org/W2904156528","https://openalex.org/W2913488954","https://openalex.org/W2964121744","https://openalex.org/W2964995401","https://openalex.org/W2986176093","https://openalex.org/W2987219395","https://openalex.org/W3098400049"],"related_works":["https://openalex.org/W2970845521","https://openalex.org/W2772628444","https://openalex.org/W4220714703","https://openalex.org/W1484355083","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W2358418295","https://openalex.org/W2497939785","https://openalex.org/W4376854386","https://openalex.org/W2735929803"],"abstract_inverted_index":{"Cold-start":[0],"is":[1,30,51,102],"a":[2,25,65,120],"long-standing":[3],"and":[4,111],"challenging":[5],"problem":[6],"in":[7,47,77,88,95],"recommendation":[8,16],"systems.":[9],"To":[10],"tackle":[11],"this":[12,61],"issue,":[13],"many":[14],"cross-domain":[15,72,130],"approaches":[17],"are":[18,117],"proposed.":[19],"However,":[20],"most":[21],"of":[22,41,128],"them":[23],"follow":[24],"two-stage":[26],"embedding-and-mapping":[27],"paradigm,":[28],"which":[29,70],"hard":[31],"to":[32,53,74],"be":[33],"optimized.":[34],"Besides,":[35],"they":[36],"ignore":[37],"the":[38,42,49,55,107,113],"structure":[39],"information":[40,94],"user-item":[43,96],"interaction":[44,97],"graph,":[45],"resulting":[46],"that":[48,133],"embedding":[50],"insufficient":[52],"capture":[54],"latent":[56],"collaborative":[57,93],"filtering":[58],"effect.":[59],"In":[60],"paper,":[62],"we":[63],"propose":[64],"Dual":[66],"Autoencoder":[67],"Network":[68],"(DAN),":[69],"implements":[71],"recommendations":[73],"cold-start":[75],"users":[76],"an":[78],"end-to-end":[79],"manner.":[80],"The":[81,99],"graph":[82],"convolutional":[83],"network":[84],"(GCN)":[85],"based":[86],"encoder":[87],"DAN":[89,134],"explicitly":[90],"captures":[91],"high-order":[92],"graphs.":[98],"two-branched":[100],"decoder":[101],"proposed":[103],"for":[104],"fully":[105],"exploiting":[106],"data":[108],"across":[109],"domains,":[110],"therefore":[112],"elaborate":[114],"reconstruction":[115],"constraints":[116],"obtained":[118],"under":[119],"domain":[121],"swapping":[122],"strategy.":[123],"Experiments":[124],"on":[125],"two":[126],"pairs":[127],"real-world":[129],"datasets":[131],"demonstrate":[132],"outperforms":[135],"existing":[136],"state-of-the-art":[137],"methods.":[138]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}