{"id":"https://openalex.org/W4213005048","doi":"https://doi.org/10.1145/3488560.3498522","title":"Community Trend Prediction on Heterogeneous Graph in E-commerce","display_name":"Community Trend Prediction on Heterogeneous Graph in E-commerce","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W4213005048","doi":"https://doi.org/10.1145/3488560.3498522"},"language":"en","primary_location":{"id":"doi:10.1145/3488560.3498522","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498522","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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/A5102975434","display_name":"Jiahao Yuan","orcid":"https://orcid.org/0009-0007-7808-2068"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiahao Yuan","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032277491","display_name":"Zhao Li","orcid":"https://orcid.org/0000-0002-5056-0351"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhao Li","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068758185","display_name":"Pengcheng Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengcheng Zou","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114546926","display_name":"Xuan Gao","orcid":"https://orcid.org/0000-0003-4919-5227"},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Gao","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031118657","display_name":"Jinwei Pan","orcid":"https://orcid.org/0000-0003-2096-8601"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinwei Pan","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063737797","display_name":"Wendi Ji","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wendi Ji","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100344628","display_name":"Xiaoling Wang","orcid":"https://orcid.org/0000-0002-4594-6946"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]},{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoling Wang","raw_affiliation_strings":["East China Normal University &amp; Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University &amp; Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I66867065","https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5102975434"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":2.6205,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.90377358,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1319","last_page":"1327"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9937000274658203,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9937000274658203,"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"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9886000156402588,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9872000217437744,"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":0.8142539262771606},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7319855093955994},{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.7173919677734375},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6322406530380249},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.5137237310409546},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.44477224349975586},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4316195249557495},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3914248049259186},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.36817628145217896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36763980984687805},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3402556777000427},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0692906379699707}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8142539262771606},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7319855093955994},{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.7173919677734375},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6322406530380249},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.5137237310409546},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.44477224349975586},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4316195249557495},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3914248049259186},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.36817628145217896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36763980984687805},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3402556777000427},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0692906379699707},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488560.3498522","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498522","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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":37,"referenced_works":["https://openalex.org/W248604449","https://openalex.org/W1964080871","https://openalex.org/W1971700777","https://openalex.org/W1999996900","https://openalex.org/W2020278455","https://openalex.org/W2052420655","https://openalex.org/W2080053379","https://openalex.org/W2125547047","https://openalex.org/W2562397084","https://openalex.org/W2604847698","https://openalex.org/W2614562328","https://openalex.org/W2765876634","https://openalex.org/W2766114385","https://openalex.org/W2798538558","https://openalex.org/W2892880750","https://openalex.org/W2912083425","https://openalex.org/W2981747147","https://openalex.org/W2984373482","https://openalex.org/W2997636257","https://openalex.org/W3028772300","https://openalex.org/W3033060645","https://openalex.org/W3034714642","https://openalex.org/W3035726724","https://openalex.org/W3049690396","https://openalex.org/W3080566854","https://openalex.org/W3081170586","https://openalex.org/W3104449587","https://openalex.org/W3106521244","https://openalex.org/W3154221903","https://openalex.org/W3154875715","https://openalex.org/W3156528502","https://openalex.org/W3173365306","https://openalex.org/W3175016299","https://openalex.org/W3176857846","https://openalex.org/W3177318507","https://openalex.org/W4206255050","https://openalex.org/W4297971002"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4376608589","https://openalex.org/W1590307681","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"In":[0,67],"online":[1],"shopping,":[2],"ever-changing":[3],"fashion":[4,159],"trends":[5],"make":[6],"merchants":[7],"need":[8,22],"to":[9,14,23,95,116,132,156,190],"prepare":[10],"more":[11],"differentiated":[12],"products":[13],"meet":[15],"the":[16,25,33,36,40,48,58,62,73,78,88,97,118,126,134,152,158,176,179,188,192],"diversified":[17],"demands,":[18],"and":[19,81,186],"e-commerce":[20,173],"platforms":[21],"capture":[24,157],"market":[26],"trend":[27,34,60,75,99,160,194],"with":[28],"a":[29,83,101,108,130,146,171],"prophetic":[30],"vision.":[31],"For":[32],"prediction,":[35],"attribute":[37,59,80,98,138,162],"tags,":[38],"as":[39],"essential":[41],"description":[42],"of":[43,51,91,120,136,161,178],"items,":[44],"can":[45],"genuinely":[46],"reflect":[47],"decision":[49],"basis":[50],"consumers.":[52],"However,":[53],"few":[54],"existing":[55],"works":[56],"explore":[57],"in":[61,100,140,170,195],"specific":[63,102],"community":[64,74,193],"for":[65],"e-commerce.":[66],"this":[68],"paper,":[69],"we":[70,105,124,144],"focus":[71],"on":[72,77,151,166],"prediction":[76],"item":[79],"propose":[82],"unified":[84],"framework":[85],"that":[86],"combines":[87],"dynamic":[89,147],"evolution":[90,148],"two":[92],"graph":[93,111,128],"patterns":[94],"predict":[96],"community.":[103,142],"Specifically,":[104],"first":[106],"design":[107],"community-attribute":[109],"bipartite":[110,127],"at":[112],"each":[113],"time":[114],"step":[115],"learn":[117],"collaboration":[119],"different":[121,137],"communities.":[122],"Next,":[123],"transform":[125],"into":[129],"hypergraph":[131],"exploit":[133],"associations":[135],"tags":[139],"one":[141],"Lastly,":[143],"introduce":[145],"component":[149],"based":[150],"recurrent":[153],"neural":[154],"networks":[155],"tags.":[163],"Extensive":[164],"experiments":[165],"three":[167],"real-world":[168],"datasets":[169],"large":[172],"platform":[174],"show":[175],"superiority":[177],"proposed":[180],"approach":[181],"over":[182],"several":[183],"strong":[184],"alternatives":[185],"demonstrate":[187],"ability":[189],"discover":[191],"advance.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
