{"id":"https://openalex.org/W2766523227","doi":"https://doi.org/10.1504/ijmso.2017.10008638","title":"Expert system for coffee rust detection based on supervised learning and graph pattern matching","display_name":"Expert system for coffee rust detection based on supervised learning and graph pattern matching","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2766523227","doi":"https://doi.org/10.1504/ijmso.2017.10008638","mag":"2766523227"},"language":"en","primary_location":{"id":"doi:10.1504/ijmso.2017.10008638","is_oa":true,"landing_page_url":"http://doi.org/10.1504/ijmso.2017.10008638","pdf_url":"https://doi.org/10.1504/ijmso.2017.10008638","source":{"id":"https://openalex.org/S25332842","display_name":"International Journal of Metadata Semantics and Ontologies","issn_l":"1744-2621","issn":["1744-2621","1744-263X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Metadata, Semantics and Ontologies","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://doi.org/10.1504/ijmso.2017.10008638","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088624122","display_name":"J.C. Corrales","orcid":"https://orcid.org/0000-0002-0096-4913"},"institutions":[{"id":"https://openalex.org/I152650591","display_name":"University of Cauca","ror":"https://ror.org/04fybn584","country_code":"CO","type":"education","lineage":["https://openalex.org/I152650591"]}],"countries":["CO"],"is_corresponding":true,"raw_author_name":"Juan Carlos Corrales","raw_affiliation_strings":["University of Cauca, Popay\u00e1n, Colombia"],"affiliations":[{"raw_affiliation_string":"University of Cauca, Popay\u00e1n, Colombia","institution_ids":["https://openalex.org/I152650591"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055420609","display_name":"Emmanuel Lasso","orcid":"https://orcid.org/0000-0002-4950-5048"},"institutions":[{"id":"https://openalex.org/I152650591","display_name":"University of Cauca","ror":"https://ror.org/04fybn584","country_code":"CO","type":"education","lineage":["https://openalex.org/I152650591"]}],"countries":["CO"],"is_corresponding":false,"raw_author_name":"Emmanuel Lasso","raw_affiliation_strings":["Telematics Engineering Group, University of Cauca, Popay\u00e1n, Colombia"],"affiliations":[{"raw_affiliation_string":"Telematics Engineering Group, University of Cauca, Popay\u00e1n, Colombia","institution_ids":["https://openalex.org/I152650591"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112080947","display_name":"Carlos Alberto Alves Meira","orcid":null},"institutions":[{"id":"https://openalex.org/I199691007","display_name":"Brazilian Agricultural Research Corporation","ror":"https://ror.org/0482b5b22","country_code":"BR","type":"government","lineage":["https://openalex.org/I199691007"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Carlos Alberto Alves Meira","raw_affiliation_strings":["Embrapa Agricultural Informatics, Campinas, S\u00e3o Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"Embrapa Agricultural Informatics, Campinas, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I199691007"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072852247","display_name":"Thiago Toshiyuki Thamada","orcid":null},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Thiago Toshiyuki Thamada","raw_affiliation_strings":["University of Campinas, Campinas, S\u00e3o Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"University of Campinas, Campinas, S\u00e3o Paulo, Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5088624122"],"corresponding_institution_ids":["https://openalex.org/I152650591"],"apc_list":null,"apc_paid":null,"fwci":0.5563,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.6924322,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"12","issue":"1","first_page":"19","last_page":"19"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11264","display_name":"Coffee research and impacts","score":0.9714000225067139,"subfield":{"id":"https://openalex.org/subfields/2736","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11264","display_name":"Coffee research and impacts","score":0.9714000225067139,"subfield":{"id":"https://openalex.org/subfields/2736","display_name":"Pharmacology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9179999828338623,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8072142601013184},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5639387369155884},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5571503043174744},{"id":"https://openalex.org/keywords/expert-system","display_name":"Expert system","score":0.5400676131248474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5106468796730042},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.507323682308197},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49692419171333313},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4289878010749817},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4269852936267853},{"id":"https://openalex.org/keywords/pattern-matching","display_name":"Pattern matching","score":0.4187166392803192},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4116644263267517},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2941831052303314},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1654324233531952},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12180739641189575}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8072142601013184},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5639387369155884},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5571503043174744},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.5400676131248474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5106468796730042},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.507323682308197},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49692419171333313},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4289878010749817},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4269852936267853},{"id":"https://openalex.org/C68859911","wikidata":"https://www.wikidata.org/wiki/Q1503724","display_name":"Pattern matching","level":2,"score":0.4187166392803192},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4116644263267517},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2941831052303314},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1654324233531952},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12180739641189575}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijmso.2017.10008638","is_oa":true,"landing_page_url":"http://doi.org/10.1504/ijmso.2017.10008638","pdf_url":"https://doi.org/10.1504/ijmso.2017.10008638","source":{"id":"https://openalex.org/S25332842","display_name":"International Journal of Metadata Semantics and Ontologies","issn_l":"1744-2621","issn":["1744-2621","1744-263X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Metadata, Semantics and Ontologies","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1504/ijmso.2017.10008638","is_oa":true,"landing_page_url":"http://doi.org/10.1504/ijmso.2017.10008638","pdf_url":"https://doi.org/10.1504/ijmso.2017.10008638","source":{"id":"https://openalex.org/S25332842","display_name":"International Journal of Metadata Semantics and Ontologies","issn_l":"1744-2621","issn":["1744-2621","1744-263X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Metadata, Semantics and Ontologies","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2766523227.pdf","grobid_xml":"https://content.openalex.org/works/W2766523227.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W142312474","https://openalex.org/W243648312","https://openalex.org/W1489492278","https://openalex.org/W1538895598","https://openalex.org/W1887871432","https://openalex.org/W1979331609","https://openalex.org/W2009270930","https://openalex.org/W2028988099","https://openalex.org/W2042428991","https://openalex.org/W2059567605","https://openalex.org/W2062596281","https://openalex.org/W2065317638","https://openalex.org/W2080581973","https://openalex.org/W2092925611","https://openalex.org/W2106186452","https://openalex.org/W2107140775","https://openalex.org/W2123966888","https://openalex.org/W2126359798","https://openalex.org/W2131829340","https://openalex.org/W2133990480","https://openalex.org/W2147405597","https://openalex.org/W2148143831","https://openalex.org/W2149706766","https://openalex.org/W2163598528","https://openalex.org/W2180790833","https://openalex.org/W2212073654","https://openalex.org/W2229344675","https://openalex.org/W2241388380","https://openalex.org/W2313578073","https://openalex.org/W2482967919","https://openalex.org/W2611196248","https://openalex.org/W3147371910","https://openalex.org/W3171689512"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W4390569940","https://openalex.org/W2888392564","https://openalex.org/W4361193272","https://openalex.org/W4310278675","https://openalex.org/W4293151273","https://openalex.org/W2943461603","https://openalex.org/W3210429500","https://openalex.org/W3217252310","https://openalex.org/W4286894112"],"abstract_inverted_index":{"Diseases":[0],"in":[1,20],"agricultural":[2],"production":[3],"systems":[4],"represent":[5],"one":[6],"of":[7,11,39,47,55],"the":[8,32,37,78],"main":[9,33],"reasons":[10],"losses":[12],"and":[13,27,58,70],"poor-quality":[14],"products.":[15],"For":[16],"coffee":[17,40,51],"production,":[18],"experts":[19],"this":[21],"area":[22],"suggest":[23],"that":[24,35],"weather":[25],"conditions":[26],"crop":[28],"physical":[29],"properties":[30],"are":[31,81],"variables":[34],"determine":[36],"development":[38],"rust.":[41],"This":[42],"paper":[43],"proposes":[44],"an":[45,84],"extraction":[46],"rules":[48,80],"to":[49,63],"detect":[50],"rust":[52],"from":[53],"induction":[54],"decision":[56],"trees":[57],"expert":[59,85],"knowledge.":[60],"In":[61],"order":[62],"obtain":[64],"a":[65,72],"model":[66],"with":[67],"greater":[68],"expressiveness":[69],"interpretability,":[71],"graph-based":[73],"representation":[74],"is":[75],"proposed.":[76],"Finally,":[77],"extracted":[79],"evaluated":[82],"using":[83],"system":[86],"supported":[87],"on":[88],"graph":[89],"pattern":[90],"matching.":[91]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}