乐胖代购免代理版

{"id":"https://openalex.org/W2000008745","doi":"https://doi.org/10.1142/s0218001406005022","title":"LEARNING GRAPHS FROM EXAMPLES: AN APPLICATION TO THE PREDICTION OF THE TOXICITY OF CHEMICAL COMPOUNDS","display_name":"LEARNING GRAPHS FROM EXAMPLES: AN APPLICATION TO THE PREDICTION OF THE TOXICITY OF CHEMICAL COMPOUNDS","publication_year":2006,"publication_date":"2006-09-01","ids":{"openalex":"https://openalex.org/W2000008745","doi":"https://doi.org/10.1142/s0218001406005022","mag":"2000008745"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001406005022","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_indexed_in_scopus":true,"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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-article","indexed_in":["crossref"],"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/A5082731857","display_name":"Pasquale Foggia","orcid":"https://orcid.org/0000-0002-7096-1902"},"institutions":[],"countries":["IT"],"is_corresponding":false,"raw_author_name":"PASQUALE FOGGIA","raw_affiliation_strings":["Dipartimento di Informatica e Sistemistica, Universit\u00e1 di Napoli \"Federico II\", Via Claudio 21 I-80125 Napoli, Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Informatica e Sistemistica, Universit\u00e1 di Napoli \"Federico II\", Via Claudio 21 I-80125 Napoli, Italy","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058575286","display_name":"Alessandro Limongiello","orcid":null},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"funder","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"ALESSANDRO LIMONGIELLO","raw_affiliation_strings":["Dipartimento di Ingegneria dell'Informazione ed Ingegneria Elettrica, Universit\u00e1 di Salerno City, P.te Don Melillo 1 I-84084 Fisciano (SA), Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell'Informazione ed Ingegneria Elettrica, Universit\u00e1 di Salerno City, P.te Don Melillo 1 I-84084 Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075203428","display_name":"Francesco Tufano","orcid":"https://orcid.org/0000-0001-5557-5336"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"funder","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"FRANCESCO TUFANO","raw_affiliation_strings":["Dipartimento di Ingegneria dell'Informazione ed Ingegneria Elettrica, Universit\u00e1 di Salerno City, P.te Don Melillo 1 I-84084 Fisciano (SA), Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell'Informazione ed Ingegneria Elettrica, Universit\u00e1 di Salerno City, P.te Don Melillo 1 I-84084 Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110251352","display_name":"M. Vento","orcid":null},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"funder","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"MARIO VENTO","raw_affiliation_strings":["Dipartimento di Ingegneria dell'Informazione ed Ingegneria Elettrica, Universit\u00e1 di Salerno City, P.te Don Melillo 1 I-84084 Fisciano (SA), Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Ingegneria dell'Informazione ed Ingegneria Elettrica, Universit\u00e1 di Salerno City, P.te Don Melillo 1 I-84084 Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.303,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":2,"citation_normalized_percentile":{"value":0.475642,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":68,"max":72},"biblio":{"volume":"20","issue":"06","first_page":"883","last_page":"896"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.9892,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10211","display_name":"Computational Drug Discovery Methods","score":0.9892,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9133,"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/T10908","display_name":"Analytical Chemistry and Chromatography","score":0.9032,"subfield":{"id":"https://openalex.org/subfields/1607","display_name":"Spectroscopy"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.46322063}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7657629},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6715503},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.659069},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6589426},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.63316333},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.5687131},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.46322063},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38452637},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001406005022","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_indexed_in_scopus":true,"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":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.59}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":11,"referenced_works":["https://openalex.org/W1554674240","https://openalex.org/W1579313487","https://openalex.org/W1998020572","https://openalex.org/W1999138184","https://openalex.org/W2067642555","https://openalex.org/W2110377720","https://openalex.org/W2119831128","https://openalex.org/W2124996875","https://openalex.org/W2157839714","https://openalex.org/W2170589060","https://openalex.org/W2520858206"],"related_works":["https://openalex.org/W4297845793","https://openalex.org/W4280575929","https://openalex.org/W3201070945","https://openalex.org/W2963456518","https://openalex.org/W2963058055","https://openalex.org/W2898291644","https://openalex.org/W2799803467","https://openalex.org/W2753840555","https://openalex.org/W2352907195","https://openalex.org/W2166162971"],"abstract_inverted_index":{"A":[0],"common":[1],"problem":[2],"encountered":[3],"in":[4,72],"structural":[5,45],"pattern":[6],"recognition":[7],"is":[8,52,94],"the":[9,24,27,32,50,70,73,78,95,98],"difficulty":[10],"of":[11,20,26,41,49,97,101],"constructing":[12],"classification":[13],"models":[14],"or":[15],"rules":[16],"from":[17,69],"a":[18,42],"set":[19],"examples,":[21],"due":[22],"to":[23,30,53,65,89],"complexity":[25],"structures":[28],"needed":[29],"represent":[31],"patterns.":[33],"In":[34],"this":[35],"paper,":[36],"we":[37],"present":[38],"an":[39],"extension":[40],"method":[43,51,85],"for":[44],"learning.":[46],"The":[47],"goal":[48],"find":[54],"descriptions":[55],"which":[56],"are":[57,62],"general":[58],"(in":[59],"other":[60],"words,":[61],"successfully":[63],"applicable":[64],"recognize":[66],"objects":[67],"different":[68],"ones":[71],"training":[74],"set),":[75],"preserving":[76],"at":[77],"same":[79],"time":[80],"their":[81],"discrimination":[82],"ability.":[83],"This":[84],"has":[86],"been":[87],"applied":[88],"predictive":[90],"toxicology":[91],"evaluation,":[92],"that":[93],"inference":[96],"cancerogenic":[99],"characteristics":[100],"chemical":[102],"compounds.":[103]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2000008745","counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-03-20T23:29:18.295633","created_date":"2016-06-24"}