{"id":"https://openalex.org/W7125962475","doi":"https://doi.org/10.1109/smc58881.2025.11343020","title":"ALSGCN: An Attention-based Long- and Short-term Graph Convolutional Network for Stock Recommendation","display_name":"ALSGCN: An Attention-based Long- and Short-term Graph Convolutional Network for Stock Recommendation","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125962475","doi":"https://doi.org/10.1109/smc58881.2025.11343020"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5124118489","display_name":"Junpeng Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junpeng Yu","raw_affiliation_strings":["Jinan University,College of Information Science and Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Jinan University,College of Information Science and Technology,Guangzhou,China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124064486","display_name":"Wenjie Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjie Yao","raw_affiliation_strings":["Jinan University,College of Information Science and Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Jinan University,College of Information Science and Technology,Guangzhou,China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380117","display_name":"Zhihao Li","orcid":"https://orcid.org/0000-0001-8085-8530"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihao Li","raw_affiliation_strings":["Jinan University,College of Information Science and Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Jinan University,College of Information Science and Technology,Guangzhou,China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055404412","display_name":"Lele Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lele Gao","raw_affiliation_strings":["Jinan University,College of Information Science and Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Jinan University,College of Information Science and Technology,Guangzhou,China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124057443","display_name":"Wenyun Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenyun Xiao","raw_affiliation_strings":["Jinan University,College of Information Science and Technology,Guangzhou,China"],"affiliations":[{"raw_affiliation_string":"Jinan University,College of Information Science and Technology,Guangzhou,China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009287950","display_name":"Hongnian Wang","orcid":"https://orcid.org/0000-0002-7543-3957"},"institutions":[{"id":"https://openalex.org/I105086349","display_name":"North Sichuan Medical University","ror":"https://ror.org/05k3sdc46","country_code":"CN","type":"education","lineage":["https://openalex.org/I105086349"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongnian Wang","raw_affiliation_strings":["North Sichuan Medical College,Key Laboratory of Digital-Intelligent Disease Surveillance and Health Governance,Nanchong,China"],"affiliations":[{"raw_affiliation_string":"North Sichuan Medical College,Key Laboratory of Digital-Intelligent Disease Surveillance and Health Governance,Nanchong,China","institution_ids":["https://openalex.org/I105086349"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5124118489"],"corresponding_institution_ids":["https://openalex.org/I159948400"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.79570826,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3186","last_page":"3191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.7777000069618225,"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"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.7777000069618225,"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"}},{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.07090000063180923,"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":0.02590000070631504,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.520799994468689},{"id":"https://openalex.org/keywords/interdependence","display_name":"Interdependence","score":0.4593000113964081},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4528999924659729},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3756999969482422},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.3693000078201294},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.30730000138282776}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7226999998092651},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.520799994468689},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4860999882221222},{"id":"https://openalex.org/C185874996","wikidata":"https://www.wikidata.org/wiki/Q269699","display_name":"Interdependence","level":2,"score":0.4593000113964081},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4528999924659729},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3756999969482422},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3693000078201294},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34139999747276306},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3264000117778778},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30090001225471497},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.29429998993873596},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2831000089645386},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343020","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343020","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5337181091308594,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1969852690","https://openalex.org/W2007358469","https://openalex.org/W2064675550","https://openalex.org/W2526849907","https://openalex.org/W2865675487","https://openalex.org/W2893230400","https://openalex.org/W2945302307","https://openalex.org/W2946170292","https://openalex.org/W2963608065","https://openalex.org/W2964413206","https://openalex.org/W3006768287","https://openalex.org/W3080253043","https://openalex.org/W3123007418","https://openalex.org/W3131543199","https://openalex.org/W3172807453","https://openalex.org/W3175177406","https://openalex.org/W3202315245","https://openalex.org/W4226142228","https://openalex.org/W4292696884","https://openalex.org/W4365393228","https://openalex.org/W4388766713","https://openalex.org/W4389117490","https://openalex.org/W4390675555","https://openalex.org/W4400291552","https://openalex.org/W4402619928","https://openalex.org/W4416250426"],"related_works":[],"abstract_inverted_index":{"Stock":[0],"recommendation":[1],"plays":[2],"a":[3,88,124],"critical":[4],"role":[5],"in":[6],"financial":[7],"investment":[8],"decision-making.":[9],"In":[10],"real-world":[11,137],"markets,":[12],"stocks":[13],"exhibit":[14],"complex":[15],"interdependencies":[16],"through":[17,83,123],"correlated":[18],"price":[19,34],"movements.":[20],"Existing":[21],"approaches":[22,44],"derive":[23],"stock":[24,76,81],"relationships":[25,82],"either":[26],"from":[27,55],"fundamental":[28],"information":[29,113],"(e.g.,":[30],"industry":[31],"categories)":[32],"or":[33],"temporal":[35,57,106],"patterns.":[36],"However,":[37],"these":[38,62],"methods":[39],"face":[40],"limitations:":[41],"domain":[42],"expertise-based":[43],"fail":[45],"to":[46],"capture":[47],"implicit":[48],"correlations,":[49],"while":[50],"short-term":[51],"relationship":[52,119],"modeling":[53],"suffers":[54],"inadequate":[56],"feature":[58,107,131],"representation.":[59],"To":[60],"address":[61],"challenges,":[63],"we":[64],"propose":[65],"ALSGCN,":[66],"an":[67,104],"Attention-based":[68],"Long-":[69],"and":[70,102],"Short-term":[71],"Graph":[72],"Convolutional":[73],"Network":[74],"for":[75,129],"recommendation.":[77],"ALSGCN":[78,141],"captures":[79],"dynamic":[80],"two":[84,136],"key":[85],"components:":[86],"(1)":[87],"market-aware":[89],"mechanism":[90],"that":[91,110,140],"models":[92],"long-term":[93],"dependencies":[94],"by":[95],"incorporating":[96],"the":[97],"influence":[98],"of":[99],"large-cap":[100],"stocks,":[101],"(2)":[103],"attention-based":[105],"extraction":[108],"module":[109,128],"adaptively":[111],"weights":[112],"across":[114,146],"time":[115],"steps.":[116],"These":[117],"complementary":[118],"representations":[120],"are":[121],"integrated":[122],"multichannel":[125],"graph":[126],"attention":[127],"effective":[130],"learning.":[132],"Extensive":[133],"experiments":[134],"on":[135],"datasets":[138],"demonstrate":[139],"consistently":[142],"outperforms":[143],"state-of-the-art":[144],"baselines":[145],"most":[147],"evaluation":[148],"metrics.":[149],"Code":[150],"is":[151],"available":[152],"at":[153],"https://github.com/hongnianwang/ALSGCN.":[154]},"counts_by_year":[],"updated_date":"2026-01-29T23:17:01.242718","created_date":"2026-01-29T00:00:00"}
