{"id":"https://openalex.org/W2580838704","doi":"https://doi.org/10.1142/s0218001417500276","title":"Learning Similarity Scores by Using a Family of Distance Functions in Multiple Feature Spaces","display_name":"Learning Similarity Scores by Using a Family of Distance Functions in Multiple Feature Spaces","publication_year":2017,"publication_date":"2017-01-26","ids":{"openalex":"https://openalex.org/W2580838704","doi":"https://doi.org/10.1142/s0218001417500276","mag":"2580838704"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001417500276","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001417500276","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.1142/S0218001417500276","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5070554674","display_name":"Emilia L\u00f3pez-I\u00f1esta","orcid":"https://orcid.org/0000-0002-1325-2501"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Emilia L\u00f3pez-I\u00f1esta","raw_affiliation_strings":["Departament d\u2019Inform\u00e0tica, Universitat de Val\u00e8ncia, Av. de la Universitat, s/n. 46100-Burjassot, Spain"],"affiliations":[{"raw_affiliation_string":"Departament d\u2019Inform\u00e0tica, Universitat de Val\u00e8ncia, Av. de la Universitat, s/n. 46100-Burjassot, Spain","institution_ids":["https://openalex.org/I16097986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050653653","display_name":"Francisco Grimaldo","orcid":"https://orcid.org/0000-0002-1357-7170"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Francisco Grimaldo","raw_affiliation_strings":["Departament d\u2019Inform\u00e0tica, Universitat de Val\u00e8ncia, Av. de la Universitat, s/n. 46100-Burjassot, Spain"],"affiliations":[{"raw_affiliation_string":"Departament d\u2019Inform\u00e0tica, Universitat de Val\u00e8ncia, Av. de la Universitat, s/n. 46100-Burjassot, Spain","institution_ids":["https://openalex.org/I16097986"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061463962","display_name":"Miguel Arevalillo\u2010Herr\u00e1ez","orcid":"https://orcid.org/0000-0002-0350-2079"},"institutions":[{"id":"https://openalex.org/I16097986","display_name":"Universitat de Val\u00e8ncia","ror":"https://ror.org/043nxc105","country_code":"ES","type":"education","lineage":["https://openalex.org/I16097986"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Miguel Arevalillo-Herr\u00e1ez","raw_affiliation_strings":["Departament d\u2019Inform\u00e0tica, Universitat de Val\u00e8ncia, Av. de la Universitat, s/n. 46100-Burjassot, Spain"],"affiliations":[{"raw_affiliation_string":"Departament d\u2019Inform\u00e0tica, Universitat de Val\u00e8ncia, Av. de la Universitat, s/n. 46100-Burjassot, Spain","institution_ids":["https://openalex.org/I16097986"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5070554674"],"corresponding_institution_ids":["https://openalex.org/I16097986"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.41825183,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"31","issue":"08","first_page":"1750027","last_page":"1750027"},"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":0.9988999962806702,"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":0.9988999962806702,"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":0.9986000061035156,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.996399998664856,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6554257869720459},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6204172372817993},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5845720767974854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5606062412261963},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5297083854675293},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5015017986297607},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47659462690353394},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4663720726966858},{"id":"https://openalex.org/keywords/similarity-learning","display_name":"Similarity learning","score":0.4491264820098877},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4393176734447479},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.42100030183792114},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.4208666682243347},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3633185625076294},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.13551628589630127}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6554257869720459},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6204172372817993},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5845720767974854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5606062412261963},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5297083854675293},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5015017986297607},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47659462690353394},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4663720726966858},{"id":"https://openalex.org/C2779597229","wikidata":"https://www.wikidata.org/wiki/Q17146505","display_name":"Similarity learning","level":3,"score":0.4491264820098877},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4393176734447479},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.42100030183792114},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.4208666682243347},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3633185625076294},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.13551628589630127},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1142/s0218001417500276","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001417500276","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:roderic.uv.es:10550/122467","is_oa":false,"landing_page_url":"https://hdl.handle.net/10550/122467","pdf_url":null,"source":{"id":"https://openalex.org/S4306400245","display_name":"Repository of Digital Objects for Teaching Research and Culture (University of Valencia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I16097986","host_organization_name":"Universitat de Val\u00e8ncia","host_organization_lineage":["https://openalex.org/I16097986"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"L\u00f3pez-I\u00f1esta, Emilia' Arevalillo-Herr\u00e1ez, Miguel Grimaldo, Francisco 2017 Learning Similarity Scores by using a family of distance functions in multiple features spaces International Journal of Pattern Recognition and Artificial Intelligence 31 8 1750027","raw_type":"journal article"},{"id":"pmh:oai:zenodo.org:18412238","is_oa":true,"landing_page_url":"https://doi.org/10.1142/S0218001417500276","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"International Journal of Pattern Recognition and Artificial Intelligence, 31(8), 1750027, (2026-01-29)","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:18412238","is_oa":true,"landing_page_url":"https://doi.org/10.1142/S0218001417500276","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"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":"International Journal of Pattern Recognition and Artificial Intelligence, 31(8), 1750027, (2026-01-29)","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4300000071525574}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321837","display_name":"Ministerio de Econom\u00eda y Competitividad","ror":"https://ror.org/034900433"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1487335190","https://openalex.org/W1516488966","https://openalex.org/W1549656520","https://openalex.org/W1603911840","https://openalex.org/W1618905105","https://openalex.org/W1628307106","https://openalex.org/W1825190116","https://openalex.org/W1965401349","https://openalex.org/W1969363575","https://openalex.org/W1978238148","https://openalex.org/W1984093344","https://openalex.org/W1990500174","https://openalex.org/W2015541566","https://openalex.org/W2019670102","https://openalex.org/W2024550919","https://openalex.org/W2030535562","https://openalex.org/W2041806006","https://openalex.org/W2046368543","https://openalex.org/W2054498688","https://openalex.org/W2055693100","https://openalex.org/W2062669091","https://openalex.org/W2069646996","https://openalex.org/W2100233488","https://openalex.org/W2100489069","https://openalex.org/W2104752854","https://openalex.org/W2106053110","https://openalex.org/W2117154949","https://openalex.org/W2117501368","https://openalex.org/W2118393783","https://openalex.org/W2127015580","https://openalex.org/W2140514860","https://openalex.org/W2149405418","https://openalex.org/W2150682024","https://openalex.org/W2152010828","https://openalex.org/W2156909104","https://openalex.org/W2158139921","https://openalex.org/W2158640603","https://openalex.org/W2158702859","https://openalex.org/W2159583439","https://openalex.org/W2164456230","https://openalex.org/W2164601418","https://openalex.org/W2165533158","https://openalex.org/W2166204480","https://openalex.org/W2167247356","https://openalex.org/W2169284845","https://openalex.org/W2169495281","https://openalex.org/W2410374670","https://openalex.org/W4211246278","https://openalex.org/W4244165801","https://openalex.org/W4248916828"],"related_works":["https://openalex.org/W2072263195","https://openalex.org/W2406660971","https://openalex.org/W2939988681","https://openalex.org/W1579730367","https://openalex.org/W3105695320","https://openalex.org/W2187633097","https://openalex.org/W2188215543","https://openalex.org/W2905174016","https://openalex.org/W3139362840","https://openalex.org/W120575082","https://openalex.org/W1528207020","https://openalex.org/W2598154258","https://openalex.org/W3207924942","https://openalex.org/W2789516530","https://openalex.org/W2336935580","https://openalex.org/W2185966459","https://openalex.org/W2738285525","https://openalex.org/W2752915819","https://openalex.org/W2171488114","https://openalex.org/W2329725455"],"abstract_inverted_index":{"There":[0],"exist":[1],"a":[2,44,53,58,63,80,91,99,109,127,147,160,179],"large":[3],"number":[4],"of":[5,28,62,65,126,129,131,162,167,207],"distance":[6,66,77,163],"functions":[7,164],"that":[8,71,133,150,192],"allow":[9],"one":[10],"to":[11,42,55,73,146,177],"measure":[12],"similarity":[13,46,59,101,118],"between":[14],"feature":[15,153],"vectors":[16,154],"and":[17,87,104,203],"thus":[18],"can":[19],"be":[20,40],"used":[21,142,176],"for":[22,79,155],"ranking":[23,60],"purposes.":[24],"When":[25],"multiple":[26,209],"representations":[27],"the":[29,75,106,121,168,193,205],"same":[30],"object":[31],"are":[32,124,140],"available,":[33],"distances":[34,86,210],"in":[35,90,116,165,200,211],"each":[36,156,166,212],"representation":[37,170,213],"space":[38],"may":[39],"combined":[41],"produce":[43],"single":[45],"score.":[47],"In":[48],"this":[49,95,173],"paper,":[50],"we":[51,83,97],"present":[52],"method":[54,195],"build":[56],"such":[57],"out":[61],"family":[64,161],"functions.":[67],"Unlike":[68],"other":[69,197],"approaches":[70,199],"aim":[72],"select":[74],"best":[76],"function":[78,149],"particular":[81],"context,":[82],"use":[84],"several":[85],"combine":[88],"them":[89],"convenient":[92],"way.":[93],"To":[94],"end,":[96],"adopt":[98],"classical":[100],"learning":[102,113,119],"approach":[103,182],"face":[105],"problem":[107],"as":[108,137,143],"standard":[110],"supervised":[111],"machine":[112],"task.":[114],"As":[115],"most":[117],"settings,":[120],"training":[122],"data":[123],"composed":[125],"set":[128],"pairs":[130],"objects":[132],"have":[134],"been":[135,184],"labeled":[136],"similar/dissimilar.":[138],"These":[139],"first":[141],"an":[144],"input":[145],"transformation":[148],"computes":[151],"new":[152],"pair":[157],"by":[158],"using":[159,186,208],"available":[169],"spaces.":[171],"Then,":[172],"information":[174],"is":[175],"learn":[178],"classifier.":[180],"The":[181],"has":[183],"tested":[185],"three":[187],"different":[188],"repositories.":[189],"Results":[190],"show":[191],"proposed":[194],"outperforms":[196],"alternative":[198],"high-dimensional":[201],"spaces":[202],"highlight":[204],"benefits":[206],"space.":[214]},"counts_by_year":[{"year":2023,"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"}
