{"id":"https://openalex.org/W7164810761","doi":"https://doi.org/10.1145/3805622.3810617","title":"Context-Aware Interpretable Representations for Retrieval and Graph Convolutional Network Classification","display_name":"Context-Aware Interpretable Representations for Retrieval and Graph Convolutional Network Classification","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164810761","doi":"https://doi.org/10.1145/3805622.3810617"},"language":null,"primary_location":{"id":"doi:10.1145/3805622.3810617","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810617","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805622.3810617","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115965059","display_name":"Thiago C\u00e9sar Castilho Almeida","orcid":"https://orcid.org/0000-0002-2167-0463"},"institutions":[{"id":"https://openalex.org/I879563668","display_name":"Universidade Estadual Paulista (Unesp)","ror":"https://ror.org/00987cb86","country_code":"BR","type":"education","lineage":["https://openalex.org/I879563668"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Thiago C\u00e9sar Castilho Almeida","raw_affiliation_strings":["UNESP - Universidade Estadual Paulista, Rio Claro, S\u00e3o Paulo, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-2167-0463","affiliations":[{"raw_affiliation_string":"UNESP - Universidade Estadual Paulista, Rio Claro, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I879563668"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093130819","display_name":"Gustavo Rosseto Let\u00edcio","orcid":"https://orcid.org/0009-0008-3715-8991"},"institutions":[{"id":"https://openalex.org/I879563668","display_name":"Universidade Estadual Paulista (Unesp)","ror":"https://ror.org/00987cb86","country_code":"BR","type":"education","lineage":["https://openalex.org/I879563668"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Gustavo Rosseto Let\u00edcio","raw_affiliation_strings":["UNESP - Universidade Estadual Paulista, Rio Claro, S\u00e3o Paulo, Brazil"],"raw_orcid":"https://orcid.org/0009-0008-3715-8991","affiliations":[{"raw_affiliation_string":"UNESP - Universidade Estadual Paulista, Rio Claro, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I879563668"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025264509","display_name":"Vinicius Atsushi Sato Kawai","orcid":null},"institutions":[{"id":"https://openalex.org/I879563668","display_name":"Universidade Estadual Paulista (Unesp)","ror":"https://ror.org/00987cb86","country_code":"BR","type":"education","lineage":["https://openalex.org/I879563668"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Vinicius Atsushi Sato Kawai","raw_affiliation_strings":["UNESP - Universidade Estadual Paulista, Rio Claro, S\u00e3o Paulo, Brazil"],"raw_orcid":"https://orcid.org/0000-0003-0153-7910","affiliations":[{"raw_affiliation_string":"UNESP - Universidade Estadual Paulista, Rio Claro, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I879563668"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078511671","display_name":"Daniel Carlos Guimar\u00e3es Pedronette","orcid":"https://orcid.org/0000-0002-2867-4838"},"institutions":[{"id":"https://openalex.org/I879563668","display_name":"Universidade Estadual Paulista (Unesp)","ror":"https://ror.org/00987cb86","country_code":"BR","type":"education","lineage":["https://openalex.org/I879563668"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Daniel Carlos Guimar\u00e3es Pedronette","raw_affiliation_strings":["UNESP - Universidade Estadual Paulista, Rio Claro, S\u00e3o Paulo, Brazil"],"raw_orcid":"https://orcid.org/0000-0002-2867-4838","affiliations":[{"raw_affiliation_string":"UNESP - Universidade Estadual Paulista, Rio Claro, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I879563668"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.94658296,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1092","last_page":"1101"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.7840999960899353,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.7840999960899353,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.06260000169277191,"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"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.018200000748038292,"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/interpretability","display_name":"Interpretability","score":0.9161999821662903},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7372000217437744},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6223999857902527},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5759000182151794},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5598000288009644},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5214999914169312},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.48669999837875366},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4519999921321869}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9161999821662903},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7372000217437744},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6492999792098999},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6492000222206116},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6223999857902527},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5759000182151794},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5598000288009644},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5214999914169312},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5055000185966492},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.48669999837875366},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4519999921321869},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4000000059604645},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.3702000081539154},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.32089999318122864},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3183000087738037},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2802000045776367},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26840001344680786},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C2780233690","wikidata":"https://www.wikidata.org/wiki/Q535347","display_name":"Transparency (behavior)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2587999999523163}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805622.3810617","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810617","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805622.3810617","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810617","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.5923469662666321,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[{"id":"https://openalex.org/G4545909794","display_name":null,"funder_award_id":"2023/00095-3","funder_id":"https://openalex.org/F4320322468","funder_display_name":"Petrobras"},{"id":"https://openalex.org/G586745645","display_name":null,"funder_award_id":"313193/2023-1","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"},{"id":"https://openalex.org/F4320322468","display_name":"Petrobras","ror":"https://ror.org/0235kyq22"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W1928328839","https://openalex.org/W1977295328","https://openalex.org/W2080955644","https://openalex.org/W2150856297","https://openalex.org/W2154851992","https://openalex.org/W2163922914","https://openalex.org/W2194775991","https://openalex.org/W2499468060","https://openalex.org/W2620198059","https://openalex.org/W2889326414","https://openalex.org/W2910027896","https://openalex.org/W2945976633","https://openalex.org/W2950816581","https://openalex.org/W2962756421","https://openalex.org/W2971865858","https://openalex.org/W3012225760","https://openalex.org/W3089108230","https://openalex.org/W3117762922","https://openalex.org/W3135685797","https://openalex.org/W3138516171","https://openalex.org/W3188008942","https://openalex.org/W3202988816","https://openalex.org/W4280625772","https://openalex.org/W4290876361","https://openalex.org/W4308233826","https://openalex.org/W4312443924","https://openalex.org/W4312533318","https://openalex.org/W4313011446","https://openalex.org/W4313201671","https://openalex.org/W4386075969","https://openalex.org/W4388928904","https://openalex.org/W4400188660","https://openalex.org/W4400447518","https://openalex.org/W4401067703","https://openalex.org/W4407196382","https://openalex.org/W4409166579","https://openalex.org/W4416250601"],"related_works":[],"abstract_inverted_index":{"The":[0,139],"advances":[1],"in":[2,89,181,185],"visual":[3],"information":[4,126],"modeling":[5],"and":[6,21,35,86,133,150,160,172,188],"representation":[7],"during":[8],"the":[9,30,45,55,59,63,124,128],"last":[10],"decades":[11],"are":[12],"remarkable,":[13],"mainly":[14],"supported":[15],"by":[16,121],"Convolutional":[17,193],"Neural":[18],"Networks,":[19],"Transformer-based,":[20],"Foundation":[22],"Models.":[23],"Despite":[24],"this":[25,97],"progress,":[26],"critical":[27],"challenges":[28],"regarding":[29],"nature":[31],"of":[32,58,127],"similarity":[33],"assessment":[34],"model":[36],"transparency":[37],"have":[38],"been":[39],"neglected.":[40],"A":[41],"primary":[42],"concern":[43],"is":[44],"Geometric":[46],"Gap,":[47],"where":[48],"traditional":[49],"pairwise":[50],"measures":[51],"fail":[52],"to":[53,77,80],"capture":[54],"intrinsic":[56,170],"geometry":[57],"dataset":[60,129],"manifold.":[61],"Furthermore,":[62],"Interpretability":[64],"Gap":[65],"persists,":[66],"as":[67],"representations":[68,81,166],"often":[69],"lack":[70],"alignment":[71],"with":[72,110],"human":[73],"cognition.":[74],"Therefore,":[75],"how":[76],"provide":[78,169],"interpretability":[79,171],"while":[82],"maintaining":[83],"low":[84],"dimensionality":[85,173],"high":[87],"effectiveness":[88,180],"downstream":[90,182],"tasks":[91],"remains":[92],"an":[93],"open":[94],"challenge.":[95],"In":[96],"paper,":[98],"we":[99],"propose":[100],"a":[101,143],"novel":[102],"unsupervised":[103],"framework":[104],"that":[105,163],"integrates":[106],"Manifold":[107,148],"Learning":[108,149,152],"strategies":[109],"Rank-based":[111],"Interpretable":[112],"Graph":[113,192],"Embeddings.":[114],"Our":[115],"approach":[116,141],"effectively":[117],"bridges":[118],"these":[119],"gaps":[120],"first":[122],"characterizing":[123],"contextual":[125],"through":[130],"manifold":[131],"analysis":[132],"subsequently":[134],"generating":[135],"sparse,":[136],"self-explainable":[137],"embeddings.":[138],"proposed":[140],"employs":[142],"flexible":[144],"formulation,":[145],"allowing":[146],"different":[147],"Representation":[151],"strategies.":[153],"Extensive":[154],"experimental":[155],"evaluation":[156],"across":[157],"diverse":[158],"datasets":[159],"features":[161],"demonstrates":[162],"our":[164],"Context-Aware":[165],"not":[167],"only":[168],"reduction":[174],"but":[175],"also":[176],"maintain":[177],"or":[178],"enhance":[179],"tasks,":[183],"specifically":[184],"image":[186],"retrieval":[187],"semi-supervised":[189],"classification":[190],"using":[191],"Networks":[194],"(GCNs).":[195]},"counts_by_year":[],"updated_date":"2026-06-16T07:37:23.134862","created_date":"2026-06-16T00:00:00"}
