{"id":"https://openalex.org/W4385541843","doi":"https://doi.org/10.1145/3539618.3592089","title":"WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering","display_name":"WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering","publication_year":2023,"publication_date":"2023-07-18","ids":{"openalex":"https://openalex.org/W4385541843","doi":"https://doi.org/10.1145/3539618.3592089"},"language":"en","primary_location":{"id":"doi:10.1145/3539618.3592089","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3592089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research-information.bris.ac.uk/en/publications/841d490e-59d8-4876-a7de-2cfc62779bb9","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053712210","display_name":"Yankai Chen","orcid":"https://orcid.org/0000-0001-5741-2047"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Yankai Chen","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-5741-2047","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100386948","display_name":"Yifei Zhang","orcid":"https://orcid.org/0000-0003-4185-8663"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yifei Zhang","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-4185-8663","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091585620","display_name":"Meng\u2010Lin Yang","orcid":"https://orcid.org/0000-0003-2510-5282"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Menglin Yang","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-2510-5282","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036555049","display_name":"Zixing Song","orcid":"https://orcid.org/0000-0002-8871-3990"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zixing Song","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-8871-3990","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100410908","display_name":"Chen Ma","orcid":"https://orcid.org/0000-0001-7933-9813"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Chen Ma","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-7933-9813","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042251906","display_name":"Irwin King","orcid":"https://orcid.org/0000-0001-8106-6447"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Irwin King","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-8106-6447","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5053712210"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":4.9326,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.95493544,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2521","last_page":"2525"},"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9441999793052673,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8194395899772644},{"id":"https://openalex.org/keywords/generality","display_name":"Generality","score":0.7250773310661316},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7057927250862122},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.684378981590271},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6760432720184326},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5971605777740479},{"id":"https://openalex.org/keywords/on-the-fly","display_name":"On the fly","score":0.5257842540740967},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.4740029275417328},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47288861870765686},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.46447741985321045},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45537716150283813},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4404636323451996},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4228960871696472},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42145973443984985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41680869460105896},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4167192280292511},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3773248791694641},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.33947834372520447}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8194395899772644},{"id":"https://openalex.org/C2780767217","wikidata":"https://www.wikidata.org/wiki/Q5532421","display_name":"Generality","level":2,"score":0.7250773310661316},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7057927250862122},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.684378981590271},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6760432720184326},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5971605777740479},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.5257842540740967},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.4740029275417328},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47288861870765686},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.46447741985321045},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45537716150283813},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4404636323451996},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4228960871696472},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42145973443984985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41680869460105896},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4167192280292511},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3773248791694641},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.33947834372520447},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C542102704","wikidata":"https://www.wikidata.org/wiki/Q183257","display_name":"Psychotherapist","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3539618.3592089","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539618.3592089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:research-information.bris.ac.uk:openaire/841d490e-59d8-4876-a7de-2cfc62779bb9","is_oa":true,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/841d490e-59d8-4876-a7de-2cfc62779bb9","pdf_url":null,"source":{"id":"https://openalex.org/S4306400895","display_name":"Bristol Research (University of Bristol)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I36234482","host_organization_name":"University of Bristol","host_organization_lineage":["https://openalex.org/I36234482"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Chen, Y, Zhang, Y, Yang, M, Song, Z, Ma, C & King, I 2023, WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering. in SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, pp. 2521-2525. https://doi.org/10.1145/3539618.3592089","raw_type":"contributionToPeriodical"}],"best_oa_location":{"id":"pmh:oai:research-information.bris.ac.uk:openaire/841d490e-59d8-4876-a7de-2cfc62779bb9","is_oa":true,"landing_page_url":"https://research-information.bris.ac.uk/en/publications/841d490e-59d8-4876-a7de-2cfc62779bb9","pdf_url":null,"source":{"id":"https://openalex.org/S4306400895","display_name":"Bristol Research (University of Bristol)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I36234482","host_organization_name":"University of Bristol","host_organization_lineage":["https://openalex.org/I36234482"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Chen, Y, Zhang, Y, Yang, M, Song, Z, Ma, C & King, I 2023, WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering. in SIGIR '23: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. Association for Computing Machinery, pp. 2521-2525. https://doi.org/10.1145/3539618.3592089","raw_type":"contributionToPeriodical"},"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G1766074018","display_name":null,"funder_award_id":"No. 2018AAA0100204","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G434338367","display_name":null,"funder_award_id":"2018AAA0100204","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320309893","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23"},{"id":"https://openalex.org/F4320322942","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W385466589","https://openalex.org/W1639961155","https://openalex.org/W2019106840","https://openalex.org/W2062825722","https://openalex.org/W2210549170","https://openalex.org/W2807021761","https://openalex.org/W2945827670","https://openalex.org/W2964334477","https://openalex.org/W2979557588","https://openalex.org/W3015817662","https://openalex.org/W3045200674","https://openalex.org/W3072818879","https://openalex.org/W3094605801","https://openalex.org/W3100278010","https://openalex.org/W3100848837","https://openalex.org/W3153325943","https://openalex.org/W3209785184","https://openalex.org/W3212862161","https://openalex.org/W4206865191","https://openalex.org/W4220909642","https://openalex.org/W4281613206","https://openalex.org/W4283702870","https://openalex.org/W4284666445","https://openalex.org/W4286986033","https://openalex.org/W4290874961","https://openalex.org/W4290878031","https://openalex.org/W4290927888","https://openalex.org/W4362598119","https://openalex.org/W6600020652","https://openalex.org/W6601691205","https://openalex.org/W6602945829","https://openalex.org/W6803535088"],"related_works":["https://openalex.org/W2045049461","https://openalex.org/W4381094582","https://openalex.org/W1978893398","https://openalex.org/W1977906818","https://openalex.org/W2369625323","https://openalex.org/W3203147499","https://openalex.org/W2018870022","https://openalex.org/W3001243934","https://openalex.org/W3129488702","https://openalex.org/W2913720397"],"abstract_inverted_index":{"Maximizing":[0],"the":[1,17,28,34,70,78,82,94,120],"user-item":[2],"engagement":[3],"based":[4],"on":[5,69,111],"vectorized":[6],"embeddings":[7],"is":[8,41],"a":[9,59,88],"standard":[10],"procedure":[11],"of":[12,30,124],"recent":[13],"recommender":[14,105],"models.":[15],"Despite":[16],"superior":[18],"performance":[19],"for":[20,72],"item":[21],"recommendations,":[22],"these":[23],"methods":[24],"however":[25],"implicitly":[26],"deprioritize":[27],"modeling":[29],"user-wise":[31,90],"similarity":[32],"in":[33,135],"embedding":[35,97],"space;":[36],"consequently,":[37],"identifying":[38],"similar":[39],"users":[40],"underperforming,":[42],"and":[43,61,96,107,122],"additional":[44],"processing":[45],"schemes":[46],"are":[47],"usually":[48],"required":[49],"otherwise.":[50],"To":[51],"avoid":[52],"thorough":[53],"model":[54],"re-training,":[55],"we":[56],"propose":[57],"WSFE,":[58],"model-agnostic":[60],"training-free":[62],"representation":[63],"encoder,":[64],"to":[65,126],"be":[66],"flexibly":[67],"employed":[68],"fly":[71],"effective":[73],"user":[74],"segmentation.":[75],"Underpinned":[76],"by":[77],"optimal":[79],"transport":[80],"theory,":[81],"encoded":[83],"representations":[84],"from":[85],"WSFE":[86,101,125],"present":[87],"matched":[89],"similarity/distance":[91],"measurement":[92],"between":[93],"realistic":[95],"space.":[98],"We":[99],"incorporate":[100],"into":[102],"six":[103,112],"state-of-the-art":[104],"models":[106],"conduct":[108],"extensive":[109],"experiments":[110],"real-world":[113],"datasets.":[114],"The":[115],"empirical":[116],"analyses":[117],"well":[118],"demonstrate":[119],"superiority":[121],"generality":[123],"fuel":[127],"multiple":[128],"downstream":[129],"tasks":[130],"with":[131],"diverse":[132],"underlying":[133],"targets":[134],"recommendation.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":7},{"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"}
