{"id":"https://openalex.org/W2971072328","doi":"https://doi.org/10.3390/make1030055","title":"KGEARSRG: Kernel Graph Embedding on Attributed Relational SIFT-Based Regions Graph","display_name":"KGEARSRG: Kernel Graph Embedding on Attributed Relational SIFT-Based Regions Graph","publication_year":2019,"publication_date":"2019-08-28","ids":{"openalex":"https://openalex.org/W2971072328","doi":"https://doi.org/10.3390/make1030055","mag":"2971072328"},"language":"en","primary_location":{"id":"doi:10.3390/make1030055","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1030055","pdf_url":"https://www.mdpi.com/2504-4990/1/3/55/pdf?version=1568195063","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/1/3/55/pdf?version=1568195063","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5011670526","display_name":"Mario Manzo","orcid":"https://orcid.org/0000-0001-8727-9865"},"institutions":[{"id":"https://openalex.org/I127927624","display_name":"University of Naples - L'Orientale","ror":"https://ror.org/01q9h8k89","country_code":"IT","type":"education","lineage":["https://openalex.org/I127927624"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Mario Manzo","raw_affiliation_strings":["Information Technology Services, University of Naples \u201cL\u2019Orientale\u201d, 80121 Naples, Italy","Information Technology Services, University of Naples \"L'Orientale\", 80121 Naples, Italy"],"raw_orcid":"https://orcid.org/0000-0001-8727-9865","affiliations":[{"raw_affiliation_string":"Information Technology Services, University of Naples \u201cL\u2019Orientale\u201d, 80121 Naples, Italy","institution_ids":["https://openalex.org/I127927624"]},{"raw_affiliation_string":"Information Technology Services, University of Naples \"L'Orientale\", 80121 Naples, Italy","institution_ids":["https://openalex.org/I127927624"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5011670526"],"corresponding_institution_ids":["https://openalex.org/I127927624"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.7225,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.78874168,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"1","issue":"3","first_page":"962","last_page":"973"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9991999864578247,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9991999864578247,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9902999997138977,"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/T10057","display_name":"Face and Expression Recognition","score":0.9901999831199646,"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/graph-kernel","display_name":"Graph kernel","score":0.7387771010398865},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.6614185571670532},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6520406603813171},{"id":"https://openalex.org/keywords/graph-embedding","display_name":"Graph embedding","score":0.6120336651802063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6001631617546082},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5958095192909241},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5181844830513},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5159509778022766},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.4910597801208496},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4896714985370636},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.45301276445388794},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.43001246452331543},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.367228627204895},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.2919313311576843},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.26595795154571533},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.21680638194084167},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.09712421894073486}],"concepts":[{"id":"https://openalex.org/C100595998","wikidata":"https://www.wikidata.org/wiki/Q11731931","display_name":"Graph kernel","level":5,"score":0.7387771010398865},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.6614185571670532},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6520406603813171},{"id":"https://openalex.org/C75564084","wikidata":"https://www.wikidata.org/wiki/Q5597085","display_name":"Graph embedding","level":3,"score":0.6120336651802063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6001631617546082},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5958095192909241},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5181844830513},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5159509778022766},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.4910597801208496},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4896714985370636},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.45301276445388794},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.43001246452331543},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.367228627204895},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.2919313311576843},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.26595795154571533},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.21680638194084167},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.09712421894073486}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/make1030055","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1030055","pdf_url":"https://www.mdpi.com/2504-4990/1/3/55/pdf?version=1568195063","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:mdpi.com:/2504-4990/1/3/55/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/make1030055","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Machine Learning and Knowledge Extraction","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/make1030055","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make1030055","pdf_url":"https://www.mdpi.com/2504-4990/1/3/55/pdf?version=1568195063","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"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":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2971072328.pdf","grobid_xml":"https://content.openalex.org/works/W2971072328.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W5598288","https://openalex.org/W218960830","https://openalex.org/W1429496622","https://openalex.org/W1527495383","https://openalex.org/W1567068365","https://openalex.org/W1670263352","https://openalex.org/W1996828958","https://openalex.org/W2009508207","https://openalex.org/W2023473787","https://openalex.org/W2032648568","https://openalex.org/W2041406732","https://openalex.org/W2087347434","https://openalex.org/W2088950943","https://openalex.org/W2101593172","https://openalex.org/W2112973039","https://openalex.org/W2118585731","https://openalex.org/W2125055259","https://openalex.org/W2127107987","https://openalex.org/W2147286743","https://openalex.org/W2148603752","https://openalex.org/W2151103935","https://openalex.org/W3142980988","https://openalex.org/W6631769861","https://openalex.org/W6637074454","https://openalex.org/W6637939071","https://openalex.org/W6677656871","https://openalex.org/W6681837462"],"related_works":["https://openalex.org/W1592261055","https://openalex.org/W2012262020","https://openalex.org/W2056283567","https://openalex.org/W2078320823","https://openalex.org/W2971072328","https://openalex.org/W2088032561","https://openalex.org/W3018902609","https://openalex.org/W2542234468","https://openalex.org/W1565299197","https://openalex.org/W2544132760"],"abstract_inverted_index":{"In":[0,12],"real":[1],"world":[2],"applications,":[3],"binary":[4],"classification":[5,28,55],"is":[6,29,34,66,69],"often":[7],"affected":[8,82],"by":[9,83],"imbalanced":[10],"classes.":[11],"this":[13],"paper,":[14],"a":[15,37,58,72],"new":[16],"methodology":[17],"to":[18],"solve":[19],"the":[20,91,96],"class":[21],"imbalance":[22,85],"problem":[23],"that":[24,90],"occurs":[25],"in":[26],"image":[27,33],"proposed.":[30],"A":[31,54],"digital":[32],"described":[35],"through":[36,71],"novel":[38],"vector-based":[39],"representation":[40],"called":[41],"Kernel":[42],"Graph":[43,52],"Embedding":[44],"on":[45,61,77],"Attributed":[46],"Relational":[47],"Scale-Invariant":[48],"Feature":[49],"Transform-based":[50],"Regions":[51],"(KGEARSRG).":[53],"stage":[56],"using":[57],"procedure":[59],"based":[60],"support":[62],"vector":[63],"machines":[64],"(SVMs)":[65],"organized.":[67],"Methodology":[68],"evaluated":[70],"series":[73],"of":[74],"experiments":[75],"performed":[76],"art":[78],"painting":[79],"dataset":[80],"images,":[81],"varying":[84],"percentages.":[86],"Experimental":[87],"results":[88],"show":[89],"proposed":[92],"approach":[93],"consistently":[94],"outperforms":[95],"competitors.":[97]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
