{"id":"https://openalex.org/W4403780715","doi":"https://doi.org/10.1145/3664647.3681207","title":"SOIL: Contrastive Second-Order Interest Learning for Multimodal Recommendation","display_name":"SOIL: Contrastive Second-Order Interest Learning for Multimodal Recommendation","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403780715","doi":"https://doi.org/10.1145/3664647.3681207"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681207","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681207","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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/A5101588702","display_name":"Hongzu Su","orcid":"https://orcid.org/0000-0002-1464-6764"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongzu Su","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100338386","display_name":"Jingjing Li","orcid":"https://orcid.org/0000-0002-5504-2529"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjing Li","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101901063","display_name":"Fengling Li","orcid":"https://orcid.org/0000-0002-3432-6215"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Fengling Li","raw_affiliation_strings":["University of Technology Sydney, Sydney, Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology Sydney, Sydney, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079281855","display_name":"Ke L\u00fc","orcid":"https://orcid.org/0000-0002-3456-4993"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Lu","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108048954","display_name":"Lei Zhu","orcid":"https://orcid.org/0000-0002-2993-7142"},"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"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhu","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101588702"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":4.03,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.94627395,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5838","last_page":"5846"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":1.0,"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/T10028","display_name":"Topic Modeling","score":0.9969000220298767,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.6562207937240601},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.4939954876899719},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4237474799156189},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41095343232154846}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6562207937240601},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.4939954876899719},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4237474799156189},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41095343232154846},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3681207","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681207","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W52770770","https://openalex.org/W2027731328","https://openalex.org/W2119825970","https://openalex.org/W2130502756","https://openalex.org/W2742143754","https://openalex.org/W2750171493","https://openalex.org/W2765897485","https://openalex.org/W2899457523","https://openalex.org/W2913754224","https://openalex.org/W2955597675","https://openalex.org/W2963655167","https://openalex.org/W2964258748","https://openalex.org/W2969960436","https://openalex.org/W2981171802","https://openalex.org/W2982108874","https://openalex.org/W2986515219","https://openalex.org/W3031331881","https://openalex.org/W3045200674","https://openalex.org/W3093002391","https://openalex.org/W3094605801","https://openalex.org/W3099790621","https://openalex.org/W3101707147","https://openalex.org/W3153325943","https://openalex.org/W3192113933","https://openalex.org/W3205778609","https://openalex.org/W4205091644","https://openalex.org/W4226237846","https://openalex.org/W4285288414","https://openalex.org/W4297971002","https://openalex.org/W4309185982","https://openalex.org/W4322718576","https://openalex.org/W4385682046","https://openalex.org/W4387171276","https://openalex.org/W4390451911","https://openalex.org/W4393159797"],"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/W3204019825"],"abstract_inverted_index":{"Mainstream":[0],"multimodal":[1,109],"recommender":[2],"systems":[3],"are":[4,44,102],"designed":[5],"to":[6,23,59,113,122,128,188],"learn":[7,18,129],"user":[8,20,35,49,155],"interest":[9,21,36,62],"by":[10,77,149,203],"analyzing":[11],"user-item":[12,73,105,162],"interaction":[13,74,106],"graphs.":[14],"However,":[15],"what":[16],"they":[17],"about":[19],"needs":[22],"be":[24],"completed":[25],"because":[26],"historical":[27],"interactions":[28],"only":[29],"record":[30],"items":[31,43],"that":[32,183],"best":[33],"match":[34],"(i.e.,":[37],"the":[38,85,93,125,137,147,161,198],"first-order":[39,141],"interest),":[40],"while":[41],"suboptimal":[42,65],"absent.":[45],"To":[46,135],"fully":[47],"exploit":[48],"interest,":[50,79,144],"we":[51,70,117,145],"propose":[52],"a":[53,72,89],"Second-Order":[54],"Interest":[55],"Learning":[56],"(SOIL)":[57],"framework":[58,168],"retrieve":[60],"second-order":[61,78,143],"from":[63,104],"unrecorded":[64],"items.":[66,134],"In":[67,96],"this":[68],"framework,":[69],"build":[71],"graph":[75,83,91,119],"augmented":[76],"an":[80,204],"interest-aware":[81],"item-item":[82,164],"for":[84,92,154],"visual":[86],"modality,":[87],"and":[88,108,133,142,156,163],"similar":[90],"textual":[94],"modality.":[95],"our":[97,184,195],"work,":[98],"all":[99],"three":[100,126,172],"graphs":[101,127],"constructed":[103],"records":[107],"feature":[110],"similarity.":[111],"Similarly":[112],"other":[114],"graph-based":[115],"approaches,":[116],"apply":[118],"convolutional":[120],"networks":[121],"each":[123],"of":[124,131,139,206,210],"representations":[130,158],"users":[132],"improve":[136,190],"exploitation":[138],"both":[140,160],"optimize":[146],"model":[148],"implementing":[150],"contrastive":[151],"learning":[152],"modules":[153],"item":[157],"at":[159],"levels.":[165],"The":[166],"proposed":[167],"is":[169,186],"evaluated":[170],"on":[171],"real-world":[173],"public":[174],"datasets":[175],"in":[176,208],"online":[177],"shopping":[178],"scenarios.":[179],"Experimental":[180],"results":[181],"verify":[182],"method":[185,196,201],"able":[187],"significantly":[189],"prediction":[191],"performance.":[192],"For":[193],"instance,":[194],"outperforms":[197],"previous":[199],"state-of-the-art":[200],"MGCN":[202],"average":[205],"8.1%":[207],"terms":[209],"Recall@10.":[211],"Code:":[212],"https://github.com/TL-UESTC/SOIL.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}