{"id":"https://openalex.org/W3012680292","doi":"https://doi.org/10.1145/3366423.3380233","title":"TRAP: Two-level Regularized Autoencoder-based Embedding for Power-law Distributed Data","display_name":"TRAP: Two-level Regularized Autoencoder-based Embedding for Power-law Distributed Data","publication_year":2020,"publication_date":"2020-04-20","ids":{"openalex":"https://openalex.org/W3012680292","doi":"https://doi.org/10.1145/3366423.3380233","mag":"3012680292"},"language":"en","primary_location":{"id":"doi:10.1145/3366423.3380233","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380233","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3366423.3380233","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101886540","display_name":"Dongmin Park","orcid":"https://orcid.org/0000-0003-1872-9126"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Dongmin Park","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033909285","display_name":"Hwanjun Song","orcid":"https://orcid.org/0000-0002-1105-0818"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hwanjun Song","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100332530","display_name":"Minseok Kim","orcid":"https://orcid.org/0000-0003-1675-8003"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Minseok Kim","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101805827","display_name":"Jae-Gil Lee","orcid":"https://orcid.org/0000-0002-8711-7732"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Gil Lee","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101886540"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.7954,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.77620753,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1615","last_page":"1624"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9994000196456909,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9987000226974487,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.88350510597229},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8087213039398193},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6385962963104248},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4443926513195038},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41871362924575806},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.41570472717285156},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3862813413143158},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3417770564556122}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.88350510597229},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8087213039398193},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6385962963104248},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4443926513195038},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41871362924575806},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.41570472717285156},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3862813413143158},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3417770564556122}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3366423.3380233","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380233","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3366423.3380233","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3366423.3380233","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of The Web Conference 2020","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1720514416","https://openalex.org/W1888005072","https://openalex.org/W1994389483","https://openalex.org/W2000042664","https://openalex.org/W2025768430","https://openalex.org/W2050215574","https://openalex.org/W2054141820","https://openalex.org/W2084677224","https://openalex.org/W2099471712","https://openalex.org/W2135658083","https://openalex.org/W2153579005","https://openalex.org/W2154851992","https://openalex.org/W2187089797","https://openalex.org/W2241862190","https://openalex.org/W2253995343","https://openalex.org/W2393319904","https://openalex.org/W2415243320","https://openalex.org/W2605350416","https://openalex.org/W2607500032","https://openalex.org/W2739273093","https://openalex.org/W2744226525","https://openalex.org/W2808000122","https://openalex.org/W2950352474","https://openalex.org/W2962756421","https://openalex.org/W2963085847","https://openalex.org/W2963224980","https://openalex.org/W2963460103","https://openalex.org/W3103362336","https://openalex.org/W3104097132","https://openalex.org/W3105705953","https://openalex.org/W3122507327","https://openalex.org/W4246698901","https://openalex.org/W4288083766"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W4297051394","https://openalex.org/W2752972570","https://openalex.org/W2734887215","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W2932872266"],"abstract_inverted_index":{"Recently,":[0],"autoencoder":[1],"(AE)-based":[2],"embedding":[3,18,59,138,150],"approaches":[4],"have":[5],"achieved":[6],"state-of-the-art":[7,162],"performance":[8,159],"in":[9,13,57],"many":[10,29],"tasks,":[11],"especially":[12],"top-k":[14],"recommendation":[15],"with":[16,22,36,135,140],"user":[17],"or":[19],"node":[20,23],"classification":[21],"embedding.":[24,76],"However,":[25],"we":[26,70,80],"find":[27],"that":[28,83,130],"real-world":[30],"data":[31,40],"follow":[32],"the":[33,39,75,90,110,158,161],"power-law":[34],"distribution":[35],"respect":[37],"to":[38,87,117,166],"object":[41,116],"sparsity.":[42],"When":[43],"learning":[44],"AE-based":[45,137],"embeddings":[46],"of":[47,160],"these":[48],"data,":[49],"dense":[50,98],"inputs":[51,56],"move":[52],"away":[53],"from":[54,101,104],"sparse":[55,106],"an":[58],"space":[60],"even":[61],"when":[62],"they":[63],"are":[64],"highly":[65],"correlated.":[66],"This":[67],"phenomenon,":[68],"which":[69],"call":[71],"polarization,":[72],"obviously":[73],"distorts":[74],"In":[77,144],"this":[78],"paper,":[79],"propose":[81],"TRAP":[82,126,156],"leverages":[84],"two-level":[85],"regularizers":[86],"effectively":[88],"alleviate":[89],"polarization":[91],"problem.":[92],"The":[93],"macroscopic":[94],"regularizer":[95,112],"generally":[96],"prevents":[97],"input":[99,107],"objects":[100,120],"being":[102],"distant":[103],"other":[105],"objects,":[108],"and":[109,168],"microscopic":[111],"individually":[113],"attracts":[114],"each":[115],"correlated":[118],"neighbor":[119],"rather":[121],"than":[122],"uncorrelated":[123],"ones.":[124],"Importantly,":[125],"is":[127],"a":[128,141],"meta-algorithm":[129],"can":[131],"be":[132],"easily":[133],"coupled":[134],"existing":[136],"methods":[139],"simple":[142],"modification.":[143],"extensive":[145],"experiments":[146],"on":[147],"two":[148],"representative":[149],"tasks":[151],"using":[152],"six-real":[153],"world":[154],"datasets,":[155],"boosted":[157],"algorithms":[163],"by":[164],"up":[165],"31.53%":[167],"94.99%":[169],"respectively.":[170]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
