{"id":"https://openalex.org/W4411631983","doi":"https://doi.org/10.1145/3731715.3733452","title":"Towards Effective and Consistent Information Extraction for Social Recommendation: A Minimum and Sufficiency Perspective","display_name":"Towards Effective and Consistent Information Extraction for Social Recommendation: A Minimum and Sufficiency Perspective","publication_year":2025,"publication_date":"2025-06-25","ids":{"openalex":"https://openalex.org/W4411631983","doi":"https://doi.org/10.1145/3731715.3733452"},"language":"en","primary_location":{"id":"doi:10.1145/3731715.3733452","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3731715.3733452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Multimedia Retrieval","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/A5011919005","display_name":"Wenze Ma","orcid":"https://orcid.org/0009-0007-6874-3299"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenze Ma","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087635554","display_name":"Y Wang","orcid":"https://orcid.org/0009-0003-6785-6452"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuexian Wang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chenyu Sun","orcid":"https://orcid.org/0009-0000-3066-0841"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyu Sun","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081759167","display_name":"Yanmin Zhu","orcid":"https://orcid.org/0000-0001-6406-4992"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanmin Zhu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhaobo Wang","orcid":"https://orcid.org/0000-0001-8727-6998"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaobo Wang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062240654","display_name":"Xuhao Zhao","orcid":"https://orcid.org/0009-0005-7120-4857"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuhao Zhao","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012589427","display_name":"Jiadi Yu","orcid":"https://orcid.org/0000-0002-0207-9643"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiadi Yu","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007640861","display_name":"Feilong Tang","orcid":"https://orcid.org/0000-0002-1384-198X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feilong Tang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5011919005"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21011678,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"991","last_page":"999"},"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":0.9883999824523926,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9864000082015991,"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/perspective","display_name":"Perspective (graphical)","score":0.7808144688606262},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5783874988555908},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.4575677216053009},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.45610031485557556},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3547403812408447},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3318522572517395},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23657840490341187}],"concepts":[{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.7808144688606262},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5783874988555908},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.4575677216053009},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.45610031485557556},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3547403812408447},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3318522572517395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23657840490341187},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3731715.3733452","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3731715.3733452","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G1340758573","display_name":null,"funder_award_id":"62472277,62072304,62172275,62472176,62172277,","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2144487656","https://openalex.org/W2244405900","https://openalex.org/W2907827821","https://openalex.org/W2914050157","https://openalex.org/W2914721378","https://openalex.org/W2963146368","https://openalex.org/W2971600245","https://openalex.org/W3044311607","https://openalex.org/W3045200674","https://openalex.org/W3081203761","https://openalex.org/W3095937012","https://openalex.org/W3099939189","https://openalex.org/W3100324210","https://openalex.org/W3104326162","https://openalex.org/W3114652457","https://openalex.org/W3155496675","https://openalex.org/W3155928855","https://openalex.org/W3155936517","https://openalex.org/W3158371160","https://openalex.org/W3170682786","https://openalex.org/W3173151551","https://openalex.org/W3207066264","https://openalex.org/W3213068453","https://openalex.org/W4224325975","https://openalex.org/W4284688665","https://openalex.org/W4321593910","https://openalex.org/W4327668311","https://openalex.org/W4392384667","https://openalex.org/W4396734333","https://openalex.org/W4401863879","https://openalex.org/W6803947598"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2018871932","https://openalex.org/W641279757","https://openalex.org/W370975646","https://openalex.org/W1670566515","https://openalex.org/W4242022592","https://openalex.org/W596972243","https://openalex.org/W2149537132","https://openalex.org/W4313230280","https://openalex.org/W69751022"],"abstract_inverted_index":{"Social":[0,60],"recommendation":[1,16,38,107,140],"systems":[2],"leverage":[3],"both":[4,82,97],"user-user":[5],"(u-u)":[6],"social":[7,31,83,139],"relations":[8,84],"and":[9,28,32,35,55,85,88,99,120],"user-item":[10,86],"(u-i)":[11],"collaborative":[12,33],"interactions":[13],"to":[14,41,129],"improve":[15],"quality.":[17],"Despite":[18],"their":[19],"effectiveness,":[20],"existing":[21],"models":[22],"often":[23],"struggle":[24],"with":[25,105],"task-irrelevant":[26,72],"information":[27,73,92],"misalignment":[29],"between":[30],"signals":[34,80],"the":[36,106,126],"downstream":[37],"task,":[39],"leading":[40],"suboptimal":[42],"performance.":[43],"To":[44],"address":[45],"these":[46],"limitations,":[47],"we":[48],"propose":[49],"a":[50,71,90,113],"novel":[51],"framework":[52],"for":[53,59],"Effective":[54],"Consistent":[56],"Information":[57],"Extraction":[58],"Recommendation":[61],"(ECSR).":[62],"Our":[63],"approach":[64],"focuses":[65],"on":[66,136],"two":[67],"key":[68],"modules:":[69],"(1)":[70],"discarding":[74],"module":[75,94],"that":[76,95,143],"filters":[77],"out":[78],"noisy":[79],"from":[81],"interactions,":[87],"(2)":[89],"task-relevant":[91,101],"alignment":[93,104],"captures":[96],"shared":[98],"view-specific":[100],"information,":[102],"ensuring":[103],"objective.":[108],"By":[109],"integrating":[110],"them":[111],"into":[112],"unified":[114],"form,":[115],"our":[116],"method":[117],"extracts":[118],"minimal":[119],"sufficient":[121],"statistics,":[122],"which":[123],"significantly":[124],"enhance":[125],"model's":[127],"ability":[128],"predict":[130],"user":[131],"preferences.":[132],"We":[133],"validate":[134],"ECSR":[135],"three":[137],"real-world":[138],"datasets,":[141],"demonstrating":[142],"it":[144],"consistently":[145],"outperforms":[146],"state-of-the-art":[147],"baselines.":[148]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
