{"id":"https://openalex.org/W95234126","doi":null,"title":"Learning in FOL with a similarity measure","display_name":"Learning in FOL with a similarity measure","publication_year":1992,"publication_date":"1992-07-12","ids":{"openalex":"https://openalex.org/W95234126","mag":"95234126"},"language":"en","primary_location":{"id":"mag:95234126","doi":null,"is_oa":false,"landing_page_url":"https://dblp.uni-trier.de/db/conf/aaai/aaai92.html#Bisson92","pdf_url":null,"source":{"id":"https://openalex.org/S4306420577","display_name":"National Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"National Conference on Artificial Intelligence","raw_type":null},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"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/A5060859843","display_name":"Gilles Bisson","orcid":"https://orcid.org/0009-0008-3117-0826","observed_orcids":["https://orcid.org/0009-0008-3117-0826"]},"institutions":[{"id":"https://openalex.org/I102197404","display_name":"Universit\u00e9 Paris-Sud","ror":"https://ror.org/028rypz17","country_code":"FR","type":"education","lineage":["https://openalex.org/I102197404","https://openalex.org/I277688954"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210144804","display_name":"Laboratoire de Recherche en Informatique","ror":"https://ror.org/04e3ktk27","country_code":"FR","type":"facility","lineage":["https://openalex.org/I102197404","https://openalex.org/I1294671590","https://openalex.org/I1326498283","https://openalex.org/I277688954","https://openalex.org/I4210144804","https://openalex.org/I4210159245"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Gilles Bisson","raw_affiliation_strings":["Laboratoire de Recherche en Informatique, URA, CNRS, Equipe Inference et Apprentissage, Universit\u00e9 Paris-sud, Orsay Cedex, France#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratoire de Recherche en Informatique, URA, CNRS, Equipe Inference et Apprentissage, Universit\u00e9 Paris-sud, Orsay Cedex, France#TAB#","institution_ids":["https://openalex.org/I102197404","https://openalex.org/I1294671590","https://openalex.org/I4210144804"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5060859843"],"corresponding_institution_ids":["https://openalex.org/I102197404","https://openalex.org/I1294671590","https://openalex.org/I4210144804"],"apc_list":null,"apc_paid":null,"fwci":4.3692,"has_fulltext":false,"cited_by_count":93,"citation_normalized_percentile":{"value":0.93651363,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"82","last_page":"87"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.7753999829292297,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.7753999829292297,"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/T10906","display_name":"AI-based Problem Solving and Planning","score":0.02459999918937683,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.019999999552965164,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/similarity-learning","display_name":"similarity learning","score":0.9290000200271606},{"id":"https://openalex.org/keywords/first-order-logic","display_name":"first-order logic","score":0.9290000200271606},{"id":"https://openalex.org/keywords/similarity-measures","display_name":"similarity measures","score":0.8740000128746033},{"id":"https://openalex.org/keywords/generalization","display_name":"generalization","score":0.8669999837875366},{"id":"https://openalex.org/keywords/clustering","display_name":"clustering","score":0.9879999756813049},{"id":"https://openalex.org/keywords/numerical-knowledge","display_name":"numerical knowledge","score":0.671999990940094}],"concepts":[{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.6529492735862732},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6353304982185364},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6103194355964661},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6036929488182068},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5531705617904663},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5136787295341492},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5127004384994507},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4921824038028717},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.48781540989875793},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.4103120267391205},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3828142583370209},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3784920871257782},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3356434106826782},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.18273067474365234},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:95234126","doi":null,"is_oa":false,"landing_page_url":"https://dblp.uni-trier.de/db/conf/aaai/aaai92.html#Bisson92","pdf_url":null,"source":{"id":"https://openalex.org/S4306420577","display_name":"National Conference on Artificial Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"National Conference on Artificial Intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W19510426","https://openalex.org/W29170162","https://openalex.org/W42468102","https://openalex.org/W193042242","https://openalex.org/W1492582005","https://openalex.org/W1510039206","https://openalex.org/W1527883571","https://openalex.org/W1549845211","https://openalex.org/W1558733760","https://openalex.org/W1565236324","https://openalex.org/W1999138184","https://openalex.org/W2073308541","https://openalex.org/W2798909945","https://openalex.org/W2988864014","https://openalex.org/W3198166186"],"related_works":["https://openalex.org/W6983696727","https://openalex.org/W1580212926","https://openalex.org/W7098610869","https://openalex.org/W1483766546","https://openalex.org/W7096693098","https://openalex.org/W6989997947","https://openalex.org/W2404354748","https://openalex.org/W1999138184","https://openalex.org/W1822863177","https://openalex.org/W4232524643"],"abstract_inverted_index":{"There":[0],"are":[1],"still":[2],"very":[3],"few":[4],"systems":[5],"performing":[6],"a":[7,13,61,66,80,84,100,111],"Similarity":[8],"Based":[9],"Learning":[10],"and":[11,32,55,110],"using":[12,65],"First":[14],"Order":[15],"Logic":[16],"(FOL)":[17],"representation.":[18,43],"This":[19],"limitation":[20],"comes":[21,77],"from":[22,33],"the":[23,27,34,74,115],"intrinsic":[24],"complexity":[25],"of":[26,82,86,102],"learning":[28,51],"processes":[29],"in":[30,41,60,88],"FOL":[31,103],"difficulty":[35],"to":[36,79,95,105],"deal":[37],"with":[38],"numerical":[39],"knowledge":[40,109],"this":[42,45,70],"In":[44],"paper,":[46],"we":[47],"show":[48],"that":[49],"major":[50],"processes,":[52],"namely":[53],"generalizatiorl":[54],"clustering,":[56],"can":[57],"be":[58],"solved":[59],"homogeneous":[62],"way":[63],"by":[64],"similarity":[67,75],"measure.":[68],"As":[69],"measure":[71],"is":[72,99],"defined,":[73],"computation":[76],"down":[78],"problem":[81],"solving":[83],"set":[85],"equations":[87],"several":[89],"unknowns.":[90],"The":[91],"representation":[92],"language":[93],"used":[94],"express":[96,106],"our":[97],"examples":[98],"subset":[101],"allowing":[104],"both":[107],"quantitative":[108],"relevance":[112],"scale":[113],"on":[114],"predicates.":[116]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":3}],"updated_date":"2026-11-03T10:50:19.383937","created_date":"2016-06-24T00:00:00"}
