{"id":"https://openalex.org/W4412610713","doi":"https://doi.org/10.1109/hpcc64274.2024.00173","title":"Learning to Hash with Long-Short-Term Graph Neural Networks for Efficient Social Recommendation<sup>*</sup>","display_name":"Learning to Hash with Long-Short-Term Graph Neural Networks for Efficient Social Recommendation<sup>*</sup>","publication_year":2024,"publication_date":"2024-12-13","ids":{"openalex":"https://openalex.org/W4412610713","doi":"https://doi.org/10.1109/hpcc64274.2024.00173"},"language":"en","primary_location":{"id":"doi:10.1109/hpcc64274.2024.00173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcc64274.2024.00173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on High Performance Computing and Communications (HPCC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100508946","display_name":"Lin Liu","orcid":"https://orcid.org/0009-0003-5356-9014"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Liu","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,School of Software Engineering,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,School of Software Engineering,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092108813","display_name":"Boyang Liu","orcid":"https://orcid.org/0000-0002-0814-002X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Boyang Liu","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,School of Software Engineering,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,School of Software Engineering,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102741399","display_name":"Chenxu Wang","orcid":"https://orcid.org/0000-0002-8665-6953"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenxu Wang","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,School of Software Engineering, MOE KLINNS Lab,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,School of Software Engineering, MOE KLINNS Lab,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.46377005,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1290","last_page":"1297"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9966999888420105,"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":0.9966999888420105,"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":0.9954000115394592,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9853000044822693,"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/term","display_name":"Term (time)","score":0.695304274559021},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6770266890525818},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6537810564041138},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.460636705160141},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3459603786468506},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.29253315925598145},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.16563421487808228},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06196838617324829}],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.695304274559021},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6770266890525818},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6537810564041138},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.460636705160141},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3459603786468506},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.29253315925598145},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.16563421487808228},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06196838617324829},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hpcc64274.2024.00173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpcc64274.2024.00173","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on High Performance Computing and Communications (HPCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1994389483","https://openalex.org/W2130354913","https://openalex.org/W2135598826","https://openalex.org/W2336920772","https://openalex.org/W2340502990","https://openalex.org/W2605350416","https://openalex.org/W2736141399","https://openalex.org/W2740920897","https://openalex.org/W2742528903","https://openalex.org/W2783792211","https://openalex.org/W2903907841","https://openalex.org/W2914721378","https://openalex.org/W2963207245","https://openalex.org/W2964676428","https://openalex.org/W3034907508","https://openalex.org/W3042856524","https://openalex.org/W3160345923","https://openalex.org/W4221150255","https://openalex.org/W4290981837","https://openalex.org/W4309795480","https://openalex.org/W4321380694","https://openalex.org/W4362598119","https://openalex.org/W4384343088","https://openalex.org/W4390691983","https://openalex.org/W4393146134","https://openalex.org/W4394994863","https://openalex.org/W4396220739","https://openalex.org/W6631190155","https://openalex.org/W6756644646"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Social":[0],"recommendation":[1,107,116,163],"leverages":[2],"social":[3,20,41,50,78,115],"relationships":[4,21,51],"to":[5,83,200],"predict":[6],"user":[7,58,71,172],"preferences,":[8],"effectively":[9],"addressing":[10],"challenges":[11,90],"like":[12],"data":[13],"sparsity":[14],"and":[15,22,109,122,138,148,151,175,181],"cold-start":[16],"issues.":[17],"Given":[18],"that":[19,135,153,192],"user-item":[23,155],"interactions":[24,64],"can":[25,65],"be":[26],"naturally":[27],"represented":[28],"as":[29],"graph":[30,32],"structures,":[31],"neural":[33],"networks":[34],"(GNNs)":[35],"have":[36],"demonstrated":[37],"significant":[38],"success":[39],"in":[40,62,87,212],"recommendation.":[42],"However,":[43],"most":[44],"existing":[45],"approaches":[46],"predominantly":[47],"focus":[48],"on":[49,119,186],"while":[52],"overlooking":[53],"the":[54,68,74],"sequential":[55],"nature":[56],"of":[57,70,77,100],"interactions.":[59],"Temporal":[60],"information":[61,147],"these":[63,104],"significantly":[66,205],"enhance":[67],"modeling":[69],"preferences.":[72],"Additionally,":[73],"rapid":[75],"growth":[76],"media":[79],"content":[80],"has":[81],"led":[82],"an":[84,113],"exponential":[85],"increase":[86],"data,":[88],"posing":[89],"for":[91],"efficiently":[92],"retrieving":[93],"desirable":[94],"items":[95],"from":[96],"this":[97],"vast":[98],"pool":[99],"information.":[101],"To":[102],"address":[103],"dual":[105],"challenges:":[106],"performance":[108,199],"efficiency.":[110],"We":[111],"propose":[112],"efficient":[114],"method":[117],"based":[118],"hash":[120,158],"learning":[121],"long":[123],"short-term":[124,141],"representation,":[125],"termed":[126],"HLSGNN.":[127],"Our":[128],"model":[129,194],"comprises":[130],"two":[131,176,187],"key":[132],"components:":[133],"one":[134],"learns":[136],"users\u2019":[137],"items\u2019":[139],"long-and":[140],"features":[142,156],"by":[143],"incorporating":[144],"interaction":[145],"timestamp":[146],"relational":[149],"influences,":[150],"another":[152],"converts":[154],"into":[157],"codes.":[159],"Unlike":[160],"traditional":[161],"hash-based":[162],"methods,":[164],"our":[165,193],"approach":[166],"is":[167],"trained":[168],"end-to-end,":[169],"jointly":[170],"optimizing":[171],"rating":[173],"prediction":[174],"additional":[177],"constraints":[178],"(i.e.,":[179],"orthogonality":[180],"balance":[182],"constraints).":[183],"Extensive":[184],"experiments":[185],"publicly":[188],"available":[189],"datasets":[190],"demonstrate":[191],"not":[195],"only":[196],"achieves":[197],"comparable":[198],"real-valued":[201],"models":[202],"but":[203],"also":[204],"enhances":[206],"inference":[207],"efficiency,":[208],"offering":[209],"several-fold":[210],"improvements":[211],"speed.":[213]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}