{"id":"https://openalex.org/W2100451691","doi":"https://doi.org/10.1109/ijcnn.2009.5178788","title":"A cross-situational algorithm for learning a lexicon using Neural modeling fields","display_name":"A cross-situational algorithm for learning a lexicon using Neural modeling fields","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2100451691","doi":"https://doi.org/10.1109/ijcnn.2009.5178788","mag":"2100451691"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2009.5178788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},"type":"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/A5065613423","display_name":"Jos\u00e9 F. Fontanari","orcid":"https://orcid.org/0000-0001-9413-1922"},"institutions":[{"id":"https://openalex.org/I177909021","display_name":"Universidade Federal de S\u00e3o Carlos","ror":"https://ror.org/00qdc6m37","country_code":"BR","type":"education","lineage":["https://openalex.org/I177909021"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Jose F. Fontanari","raw_affiliation_strings":["Instituto de F\u00edsica de S\u00e4o Carlos, Universidade de S\u00e4o Carlos, Sao Paulo, Brazil"],"affiliations":[{"raw_affiliation_string":"Instituto de F\u00edsica de S\u00e4o Carlos, Universidade de S\u00e4o Carlos, Sao Paulo, Brazil","institution_ids":["https://openalex.org/I177909021"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008949994","display_name":"Vadim Tikhanoff","orcid":"https://orcid.org/0000-0001-5295-3928"},"institutions":[{"id":"https://openalex.org/I897542642","display_name":"University of Plymouth","ror":"https://ror.org/008n7pv89","country_code":"GB","type":"education","lineage":["https://openalex.org/I897542642"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Vadim Tikhanoff","raw_affiliation_strings":["Adaptive Behaviour and Cognition Research Group, University of Plymouth, Plymouth, UK"],"affiliations":[{"raw_affiliation_string":"Adaptive Behaviour and Cognition Research Group, University of Plymouth, Plymouth, UK","institution_ids":["https://openalex.org/I897542642"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091768977","display_name":"Angelo Cangelosi","orcid":"https://orcid.org/0000-0002-4709-2243"},"institutions":[{"id":"https://openalex.org/I897542642","display_name":"University of Plymouth","ror":"https://ror.org/008n7pv89","country_code":"GB","type":"education","lineage":["https://openalex.org/I897542642"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Angelo Cangelosi","raw_affiliation_strings":["Adaptive Behaviour and Cognition Research Group, University of Plymouth, Plymouth, UK"],"affiliations":[{"raw_affiliation_string":"Adaptive Behaviour and Cognition Research Group, University of Plymouth, Plymouth, UK","institution_ids":["https://openalex.org/I897542642"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053674167","display_name":"Leonid Perlovsky","orcid":"https://orcid.org/0000-0002-3428-2398"},"institutions":[{"id":"https://openalex.org/I2801851002","display_name":"Harvard University Press","ror":"https://ror.org/006v7bf86","country_code":"US","type":"other","lineage":["https://openalex.org/I136199984","https://openalex.org/I2801851002"]},{"id":"https://openalex.org/I1280414376","display_name":"United States Air Force Research Laboratory","ror":"https://ror.org/02e2egq70","country_code":"US","type":"facility","lineage":["https://openalex.org/I1280414376","https://openalex.org/I1330347796","https://openalex.org/I4210102105","https://openalex.org/I4389425425"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leonid I. Perlovsky","raw_affiliation_strings":["Air Force Research Laboratory, MA, USA","Harvard University, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Air Force Research Laboratory, MA, USA","institution_ids":["https://openalex.org/I1280414376"]},{"raw_affiliation_string":"Harvard University, Cambridge, MA, USA","institution_ids":["https://openalex.org/I2801851002"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5065613423"],"corresponding_institution_ids":["https://openalex.org/I177909021"],"apc_list":null,"apc_paid":null,"fwci":4.0647,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.93968889,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"869","last_page":"876"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9958000183105469,"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/T10320","display_name":"Neural Networks and Applications","score":0.9958000183105469,"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/T14394","display_name":"Cognitive Science and Education Research","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10906","display_name":"AI-based Problem Solving and Planning","score":0.9254999756813049,"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/computer-science","display_name":"Computer science","score":0.7452636957168579},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6086231470108032},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.596689760684967},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.595477819442749},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5878046751022339},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.576863706111908},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5380591154098511},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.46889203786849976},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4326103925704956},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.4237414002418518},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.17243558168411255}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7452636957168579},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6086231470108032},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.596689760684967},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.595477819442749},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5878046751022339},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.576863706111908},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5380591154098511},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.46889203786849976},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4326103925704956},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.4237414002418518},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.17243558168411255},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/ijcnn.2009.5178788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.155.4595","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.155.4595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.tech.plym.ac.uk/soc/staff/angelo/papers/IJCNN09-Fernando-IJCNN09.pdf","raw_type":"text"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/6c1663a7-17c4-43c4-b20c-f07277bf4b89","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/6c1663a7-17c4-43c4-b20c-f07277bf4b89","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fontanari, J F, Tikhanoff, V, Cangelosi, A & Perlovsky, L I 2009, 'A cross-situational algorithm for learning a lexicon using Neural Modeling Fields', pp. 1455. < http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000280591600211&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 >","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.atira.dk:publications/6c1663a7-17c4-43c4-b20c-f07277bf4b89","is_oa":false,"landing_page_url":"https://www.research.manchester.ac.uk/portal/en/publications/a-crosssituational-algorithm-for-learning-a-lexicon-using-neural-modeling-fields(6c1663a7-17c4-43c4-b20c-f07277bf4b89).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fontanari, J F, Tikhanoff, V, Cangelosi, A & Perlovsky, L I 2009, 'A cross-situational algorithm for learning a lexicon using Neural Modeling Fields', pp. 1455. < http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000280591600211&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008 >","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W28883340","https://openalex.org/W41683454","https://openalex.org/W191461621","https://openalex.org/W203060610","https://openalex.org/W1527908145","https://openalex.org/W1534521585","https://openalex.org/W1597286183","https://openalex.org/W1714490037","https://openalex.org/W1732736211","https://openalex.org/W1966942151","https://openalex.org/W1971688232","https://openalex.org/W1972707371","https://openalex.org/W1992522501","https://openalex.org/W1993750641","https://openalex.org/W1994032939","https://openalex.org/W2018139470","https://openalex.org/W2024060531","https://openalex.org/W2027116779","https://openalex.org/W2058743577","https://openalex.org/W2097988708","https://openalex.org/W2100271512","https://openalex.org/W2100341056","https://openalex.org/W2107019937","https://openalex.org/W2107331287","https://openalex.org/W2110958718","https://openalex.org/W2119745285","https://openalex.org/W2125658997","https://openalex.org/W2126329503","https://openalex.org/W2133600927","https://openalex.org/W2138655592","https://openalex.org/W2142635246","https://openalex.org/W2143987560","https://openalex.org/W2144539135","https://openalex.org/W2156917047","https://openalex.org/W2160783091","https://openalex.org/W2161288717","https://openalex.org/W2169096704","https://openalex.org/W2169538578","https://openalex.org/W2286849520","https://openalex.org/W2802416800","https://openalex.org/W3044664353","https://openalex.org/W3110909889","https://openalex.org/W3127144342","https://openalex.org/W4233047132","https://openalex.org/W4244766315","https://openalex.org/W4252108260","https://openalex.org/W4256122533","https://openalex.org/W4285719527","https://openalex.org/W4298336473","https://openalex.org/W6601169127","https://openalex.org/W6635603907","https://openalex.org/W6675905395","https://openalex.org/W6678173725","https://openalex.org/W6678449702","https://openalex.org/W6681309017","https://openalex.org/W6684783730"],"related_works":["https://openalex.org/W2165912799","https://openalex.org/W2735662278","https://openalex.org/W2382615723","https://openalex.org/W1987484445","https://openalex.org/W2623658258","https://openalex.org/W2140536630","https://openalex.org/W4311804456","https://openalex.org/W4365135359","https://openalex.org/W2115592544","https://openalex.org/W2093773434"],"abstract_inverted_index":{"Cross-situational":[0],"learning":[1,31,120],"is":[2,32,85,168],"based":[3],"on":[4],"the":[5,12,41,51,56,60,70,78,107,114,117,125,136,142,155,160,171,188,191],"idea":[6],"that":[7,27,124,157,178],"a":[8,15,129,166],"learner":[9],"can":[10],"determine":[11],"meaning":[13],"of":[14,26,50,58,77,104,113,119,138,180,183,185,190],"word":[16,167],"by":[17,101,170],"finding":[18],"something":[19],"in":[20,39,106,159],"common":[21],"across":[22],"all":[23,94,154],"observed":[24],"uses":[25],"word.":[28],"Although":[29],"cross-situational":[30,126],"usually":[33],"modeled":[34],"through":[35],"stochastic":[36,108],"guessing":[37,109],"games":[38],"which":[40],"input":[42,79],"data":[43,80],"vary":[44],"erratically":[45],"with":[46,121],"time":[47],"(or":[48],"rounds":[49],"game),":[52],"here":[53],"we":[54,176],"investigate":[55],"possibility":[57],"applying":[59],"deterministic":[61],"neural":[62],"modeling":[63],"fields":[64],"(NMF)":[65],"categorization":[66],"mechanism":[67],"to":[68,140],"infer":[69,141],"correct":[71,143,192],"object-word":[72,87,96,144,193],"mapping.":[73,145,194],"Two":[74],"different":[75],"representations":[76],"were":[81],"considered.":[82],"The":[83,146],"first":[84],"termed":[86,149],"representation":[88],"because":[89],"it":[90],"takes":[91,151],"as":[92,152],"inputs":[93,153],"possible":[95],"pairs":[97],"and":[98],"weighs":[99],"them":[100],"their":[102],"frequencies":[103],"occurrence":[105],"game.":[110],"A":[111],"re-interpretation":[112],"problem":[115],"within":[116],"perspective":[118],"noise":[122],"indicates":[123],"scenario":[127],"produces":[128],"too":[130],"low":[131],"signal-to-noise":[132],"ratio,":[133],"explaining":[134],"thus":[135],"failure":[137],"NMF":[139,186],"second":[147],"representation,":[148],"context-word,":[150],"objects":[156],"are":[158],"pupil's":[161],"visual":[162],"field":[163],"(context)":[164],"when":[165],"uttered":[169],"teacher.":[172],"In":[173],"this":[174],"case":[175],"show":[177],"use":[179],"two":[181],"levels":[182],"hierarchy":[184],"allows":[187],"inference":[189]},"counts_by_year":[{"year":2019,"cited_by_count":3},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}