{"id":"https://openalex.org/W2217869562","doi":"https://doi.org/10.1109/tip.2015.2507401","title":"Learning of Multimodal Representations With Random Walks on the Click Graph","display_name":"Learning of Multimodal Representations With Random Walks on the Click Graph","publication_year":2015,"publication_date":"2015-12-10","ids":{"openalex":"https://openalex.org/W2217869562","doi":"https://doi.org/10.1109/tip.2015.2507401","mag":"2217869562","pmid":"https://pubmed.ncbi.nlm.nih.gov/26672038"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2015.2507401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2507401","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5004882141","display_name":"Fei Wu","orcid":"https://orcid.org/0000-0003-2139-8807"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Wu","raw_affiliation_strings":["School of Computer Science and Technology, Zhejiang University,,,Hangzhou,,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhejiang University,,,Hangzhou,,China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017087561","display_name":"Xinyan Lu","orcid":"https://orcid.org/0000-0001-9305-4515"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyan Lu","raw_affiliation_strings":["School of Computer Science and Technology, Zhejiang University,,,Hangzhou,,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhejiang University,,,Hangzhou,,China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102010684","display_name":"Jun Song","orcid":"https://orcid.org/0000-0003-0659-1158"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Song","raw_affiliation_strings":["School of Computer Science and Technology, Zhejiang University,,,Hangzhou,,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhejiang University,,,Hangzhou,,China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100381753","display_name":"Shuicheng Yan","orcid":"https://orcid.org/0000-0001-8906-3777"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Shuicheng Yan","raw_affiliation_strings":["Electrical Engineering Department, National University of Singapore, Singapore#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, National University of Singapore, Singapore#TAB#","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091693456","display_name":"Zhongfei Mark Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongfei Mark Zhang","raw_affiliation_strings":["Department of Information Science and Electronic Engineering, ZheJiang University, HangZhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Science and Electronic Engineering, ZheJiang University, HangZhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100728762","display_name":"Yong Rui","orcid":"https://orcid.org/0000-0002-9142-5914"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Rui","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008666077","display_name":"Yueting Zhuang","orcid":"https://orcid.org/0000-0001-9017-2508"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueting Zhuang","raw_affiliation_strings":["School of Computer Science and Technology, Zhejiang University,,,Hangzhou,,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhejiang University,,,Hangzhou,,China","institution_ids":["https://openalex.org/I168879160"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.7755,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.96753879,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"25","issue":"2","first_page":"630","last_page":"642"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9997000098228455,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9970999956130981,"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":0.7569324970245361},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.5413335561752319},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5302757024765015},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4895559251308441},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.4583967626094818},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4561542570590973},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.42528587579727173},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4204392433166504},{"id":"https://openalex.org/keywords/click-through-rate","display_name":"Click-through rate","score":0.41585901379585266},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3740196228027344},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3472819924354553},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32065799832344055},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16701731085777283}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7569324970245361},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.5413335561752319},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5302757024765015},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4895559251308441},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.4583967626094818},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4561542570590973},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.42528587579727173},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4204392433166504},{"id":"https://openalex.org/C115174607","wikidata":"https://www.wikidata.org/wiki/Q1100934","display_name":"Click-through rate","level":2,"score":0.41585901379585266},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3740196228027344},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3472819924354553},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32065799832344055},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16701731085777283},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2015.2507401","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2015.2507401","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:26672038","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/26672038","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1523385540","https://openalex.org/W1660390307","https://openalex.org/W1663973292","https://openalex.org/W1686810756","https://openalex.org/W1969732194","https://openalex.org/W1989085630","https://openalex.org/W2012011657","https://openalex.org/W2015175493","https://openalex.org/W2024082504","https://openalex.org/W2035517574","https://openalex.org/W2038436420","https://openalex.org/W2039753120","https://openalex.org/W2047221353","https://openalex.org/W2069870183","https://openalex.org/W2071207147","https://openalex.org/W2077528174","https://openalex.org/W2082721209","https://openalex.org/W2085695154","https://openalex.org/W2090575037","https://openalex.org/W2095609079","https://openalex.org/W2097308346","https://openalex.org/W2100235303","https://openalex.org/W2106277773","https://openalex.org/W2108598243","https://openalex.org/W2112193096","https://openalex.org/W2118509786","https://openalex.org/W2123024445","https://openalex.org/W2131462252","https://openalex.org/W2132551672","https://openalex.org/W2153579005","https://openalex.org/W2154851992","https://openalex.org/W2155893237","https://openalex.org/W2157316923","https://openalex.org/W2160555926","https://openalex.org/W2162867699","https://openalex.org/W2163605009","https://openalex.org/W2164587673","https://openalex.org/W2171496719","https://openalex.org/W2184188583","https://openalex.org/W3104097132","https://openalex.org/W4212863985","https://openalex.org/W4294170691","https://openalex.org/W6606244218","https://openalex.org/W6631216910","https://openalex.org/W6637373629","https://openalex.org/W6676297131","https://openalex.org/W6678470764","https://openalex.org/W6679224782","https://openalex.org/W6682691769","https://openalex.org/W6683441042","https://openalex.org/W6684191040","https://openalex.org/W6686207219"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2922169395","https://openalex.org/W2387658907","https://openalex.org/W25098770","https://openalex.org/W2385796165"],"abstract_inverted_index":{"In":[0,67],"multimedia":[1],"information":[2],"retrieval,":[3],"most":[4],"classic":[5],"approaches":[6,30],"tend":[7],"to":[8,160,184],"represent":[9],"different":[10],"modalities":[11],"of":[12,55,106,136,166],"media":[13],"in":[14,80,115,171],"the":[15,20,25,56,60,64,72,89,104,108,113,116,122,130,133,145,167,172,179,190,217,221],"same":[16],"feature":[17],"space.":[18],"With":[19],"click":[21,57,73,78,117,173,200],"data":[22,35,65,74,170,202],"collected":[23],"from":[24,103],"users'":[26],"searching":[27],"behavior,":[28],"existing":[29,168],"take":[31],"either":[32],"one-to-one":[33],"paired":[34],"(text-image":[36],"pairs)":[37],"or":[38],"ranking":[39,44],"examples":[40],"(text-query-image":[41],"and/or":[42],"image-query-text":[43],"lists)":[45],"as":[46,75,127,129],"training":[47],"examples,":[48],"which":[49,81,148],"do":[50],"not":[51,161],"make":[52],"full":[53],"use":[54],"data,":[58],"particularly":[59],"implicit":[61],"connections":[62],"among":[63],"objects.":[66],"this":[68],"paper,":[69],"we":[70],"treat":[71],"a":[76,95,100,197],"large":[77],"graph,":[79,174],"vertices":[82,114,137],"are":[83],"images/text":[84],"queries":[85,181],"and":[86,94,138,182,205],"edges":[87],"indicate":[88],"clicks":[90],"between":[91,112,132],"an":[92],"image":[93],"query.":[96],"We":[97,188],"consider":[98],"learning":[99],"multimodal":[101,151,169],"representation":[102,135,165,192],"perspective":[105],"encoding":[107],"explicit/implicit":[109],"relevance":[110],"relationship":[111],"graph.":[118],"By":[119],"minimizing":[120],"both":[121],"truncated":[123],"random":[124,152],"walk":[125,153],"loss":[126],"well":[128],"distance":[131],"learned":[134,193],"their":[139],"corresponding":[140],"deep":[141],"neural":[142,154],"network":[143,155],"output,":[144],"proposed":[146],"model":[147],"is":[149],"named":[150],"(MRW-NN)":[156],"can":[157],"be":[158],"applied":[159],"only":[162],"learn":[163],"robust":[164],"but":[175],"also":[176],"deal":[177],"with":[178],"unseen":[180,218],"images":[183],"support":[185],"cross-modal":[186,213],"retrieval.":[187],"evaluate":[189],"latent":[191],"by":[194],"MRW-NN":[195,209],"on":[196,216],"public":[198],"large-scale":[199],"log":[201],"set":[203],"Clickture":[204],"further":[206],"show":[207],"that":[208],"achieves":[210],"much":[211],"better":[212],"retrieval":[214],"performance":[215],"queries/images":[219],"than":[220],"other":[222],"state-of-the-art":[223],"methods.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":13},{"year":2016,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}