{"id":"https://openalex.org/W4403835712","doi":"https://doi.org/10.3390/e26110911","title":"Text-Enhanced Graph Attention Hashing for Cross-Modal Retrieval","display_name":"Text-Enhanced Graph Attention Hashing for Cross-Modal Retrieval","publication_year":2024,"publication_date":"2024-10-27","ids":{"openalex":"https://openalex.org/W4403835712","doi":"https://doi.org/10.3390/e26110911","pmid":"https://pubmed.ncbi.nlm.nih.gov/39593856"},"language":"en","primary_location":{"id":"doi:10.3390/e26110911","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26110911","pdf_url":"https://www.mdpi.com/1099-4300/26/11/911/pdf?version=1730167563","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/26/11/911/pdf?version=1730167563","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017563962","display_name":"Qiang Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Zou","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"],"raw_orcid":"https://orcid.org/0009-0006-1321-0391","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002665794","display_name":"Shuli Cheng","orcid":"https://orcid.org/0000-0001-8363-8832"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuli Cheng","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"],"raw_orcid":"https://orcid.org/0000-0001-8363-8832","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030446620","display_name":"Anyu Du","orcid":"https://orcid.org/0000-0002-9744-9589"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anyu Du","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"],"raw_orcid":"https://orcid.org/0000-0002-9744-9589","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045253027","display_name":"Jiayi Chen","orcid":"https://orcid.org/0000-0003-0217-6352"},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayi Chen","raw_affiliation_strings":["College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Xinjiang University, Urumqi 830046, China","institution_ids":["https://openalex.org/I96908189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5002665794"],"corresponding_institution_ids":["https://openalex.org/I96908189"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":0.329,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.54456284,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"26","issue":"11","first_page":"911","last_page":"911"},"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":0.9936000108718872,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9837999939918518,"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":0.8155173063278198},{"id":"https://openalex.org/keywords/hash-function","display_name":"Hash function","score":0.6255965232849121},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5609021782875061},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5373603105545044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5271622538566589},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5123921036720276},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49915289878845215},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.43372780084609985},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4137873351573944},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40009018778800964},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14960232377052307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8155173063278198},{"id":"https://openalex.org/C99138194","wikidata":"https://www.wikidata.org/wiki/Q183427","display_name":"Hash function","level":2,"score":0.6255965232849121},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5609021782875061},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5373603105545044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5271622538566589},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5123921036720276},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49915289878845215},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.43372780084609985},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4137873351573944},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40009018778800964},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14960232377052307},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e26110911","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26110911","pdf_url":"https://www.mdpi.com/1099-4300/26/11/911/pdf?version=1730167563","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:39593856","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39593856","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11592578","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11592578","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11592578/pdf/entropy-26-00911.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:0fee057e7cf64ec4a734db412d7af868","is_oa":true,"landing_page_url":"https://doaj.org/article/0fee057e7cf64ec4a734db412d7af868","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 26, Iss 11, p 911 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/e26110911","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e26110911","pdf_url":"https://www.mdpi.com/1099-4300/26/11/911/pdf?version=1730167563","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4403835712.pdf","grobid_xml":"https://content.openalex.org/works/W4403835712.grobid-xml"},"referenced_works_count":50,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1924770834","https://openalex.org/W2007972815","https://openalex.org/W2143668817","https://openalex.org/W2155803963","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2266728343","https://openalex.org/W2388114291","https://openalex.org/W2604880013","https://openalex.org/W2802864907","https://openalex.org/W2894874917","https://openalex.org/W2949588459","https://openalex.org/W2997729898","https://openalex.org/W2999606372","https://openalex.org/W3012050760","https://openalex.org/W3014697397","https://openalex.org/W3017133364","https://openalex.org/W3033799362","https://openalex.org/W3034890701","https://openalex.org/W3135367836","https://openalex.org/W3138516171","https://openalex.org/W3202874825","https://openalex.org/W4210593721","https://openalex.org/W4220857054","https://openalex.org/W4282926067","https://openalex.org/W4282937884","https://openalex.org/W4285220052","https://openalex.org/W4285288078","https://openalex.org/W4286268632","https://openalex.org/W4289537403","https://openalex.org/W4304092731","https://openalex.org/W4309482398","https://openalex.org/W4323022360","https://openalex.org/W4379382581","https://openalex.org/W4380303571","https://openalex.org/W4383503840","https://openalex.org/W4384648175","https://openalex.org/W4385614537","https://openalex.org/W4385615196","https://openalex.org/W4386101359","https://openalex.org/W4386424960","https://openalex.org/W4386472960","https://openalex.org/W4386640220","https://openalex.org/W4388191759","https://openalex.org/W6684191040","https://openalex.org/W6739901393","https://openalex.org/W6770242938","https://openalex.org/W6807336976","https://openalex.org/W6839503575"],"related_works":["https://openalex.org/W2159024673","https://openalex.org/W3001987467","https://openalex.org/W2968165261","https://openalex.org/W1603161560","https://openalex.org/W1587382781","https://openalex.org/W2154676777","https://openalex.org/W2379392295","https://openalex.org/W3160965418","https://openalex.org/W2950663250","https://openalex.org/W2133252868"],"abstract_inverted_index":{"Deep":[0],"hashing":[1,189],"technology,":[2],"known":[3],"for":[4,118,166],"its":[5],"low-cost":[6],"storage":[7],"and":[8,34,51,91,131,142,169],"rapid":[9],"retrieval,":[10],"has":[11],"become":[12],"a":[13,125,132,147],"focal":[14],"point":[15],"in":[16,37,46,59,75,83,103],"cross-modal":[17,104,188],"retrieval":[18,55,94,105],"research":[19],"as":[20],"multimodal":[21,158],"data":[22,99],"continue":[23],"to":[24,42,138,155],"grow.":[25],"However,":[26],"existing":[27],"supervised":[28],"methods":[29],"often":[30],"overlook":[31],"noisy":[32],"labels":[33],"multiscale":[35,133],"features":[36],"different":[38,167],"modal":[39,149],"datasets,":[40],"leading":[41],"higher":[43],"information":[44,62,68,81,140],"entropy":[45,69,82,141],"the":[47,67,80,93,113,161,164,182],"generated":[48],"hash":[49],"codes":[50],"features,":[52],"which":[53],"reduces":[54],"performance.":[56],"The":[57],"variation":[58],"text":[60,71,84,88,127],"annotation":[61],"across":[63],"datasets":[64,179],"further":[65],"increases":[66],"during":[70],"feature":[72,85,89,128,144,150],"extraction,":[73,86],"resulting":[74],"suboptimal":[76],"outcomes.":[77],"Consequently,":[78],"reducing":[79],"supplementing":[87],"information,":[90,159],"enhancing":[92],"efficiency":[95],"of":[96,163],"large-scale":[97],"media":[98],"are":[100],"critical":[101],"challenges":[102],"research.":[106],"To":[107],"tackle":[108],"these,":[109],"this":[110],"paper":[111],"introduces":[112],"Text-Enhanced":[114],"Graph":[115],"Attention":[116],"Hashing":[117],"Cross-Modal":[119],"Retrieval":[120],"(TEGAH)":[121],"framework.":[122],"TEGAH":[123,183],"incorporates":[124],"deep":[126],"extraction":[129],"network":[130,137,152,165],"label":[134],"region":[135],"fusion":[136,151],"minimize":[139],"optimize":[143],"extraction.":[145],"Additionally,":[146],"Graph-Attention-based":[148],"is":[153],"designed":[154],"efficiently":[156],"integrate":[157],"enhance":[160],"affinity":[162],"modes,":[168],"retain":[170],"more":[171],"semantic":[172],"information.":[173],"Extensive":[174],"experiments":[175],"on":[176],"three":[177],"multilabel":[178],"demonstrate":[180],"that":[181],"framework":[184],"significantly":[185],"outperforms":[186],"state-of-the-art":[187],"methods.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}