{"id":"https://openalex.org/W1521993350","doi":"https://doi.org/10.1007/978-3-642-15825-4_21","title":"TopoART: A Topology Learning Hierarchical ART Network","display_name":"TopoART: A Topology Learning Hierarchical ART Network","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W1521993350","doi":"https://doi.org/10.1007/978-3-642-15825-4_21","mag":"1521993350"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-642-15825-4_21","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-15825-4_21","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pub.uni-bielefeld.de/record/1925596","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085684908","display_name":"Marko Tscherepanow","orcid":null},"institutions":[{"id":"https://openalex.org/I20121455","display_name":"Bielefeld University","ror":"https://ror.org/02hpadn98","country_code":"DE","type":"education","lineage":["https://openalex.org/I20121455"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Marko Tscherepanow","raw_affiliation_strings":["Applied Informatics, Bielefeld University, Universit\u00e4tsstra\u00dfe 25, 33615, Bielefeld, Germany"],"affiliations":[{"raw_affiliation_string":"Applied Informatics, Bielefeld University, Universit\u00e4tsstra\u00dfe 25, 33615, Bielefeld, Germany","institution_ids":["https://openalex.org/I20121455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5085684908"],"corresponding_institution_ids":["https://openalex.org/I20121455"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":1.9764,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.86888634,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"157","last_page":"167"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9609000086784363,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9603999853134155,"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/adaptive-resonance-theory","display_name":"Adaptive resonance theory","score":0.8178551197052002},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8034183979034424},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.7082505822181702},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5895968079566956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5874769687652588},{"id":"https://openalex.org/keywords/topology","display_name":"Topology (electrical circuits)","score":0.5856059789657593},{"id":"https://openalex.org/keywords/network-topology","display_name":"Network topology","score":0.5810229182243347},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5159388184547424},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5081450939178467},{"id":"https://openalex.org/keywords/competitive-learning","display_name":"Competitive learning","score":0.5061468482017517},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.49926161766052246},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35858380794525146},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09011033177375793},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.06038293242454529}],"concepts":[{"id":"https://openalex.org/C115755159","wikidata":"https://www.wikidata.org/wiki/Q352487","display_name":"Adaptive resonance theory","level":3,"score":0.8178551197052002},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8034183979034424},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7082505822181702},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5895968079566956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5874769687652588},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.5856059789657593},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.5810229182243347},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5159388184547424},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5081450939178467},{"id":"https://openalex.org/C120822770","wikidata":"https://www.wikidata.org/wiki/Q5156355","display_name":"Competitive learning","level":3,"score":0.5061468482017517},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.49926161766052246},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35858380794525146},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09011033177375793},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.06038293242454529},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/978-3-642-15825-4_21","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-642-15825-4_21","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.669.9847","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.669.9847","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://pub.uni-bielefeld.de/luur/download?fileOId%3D2499061%26func%3DdownloadFile%26recordOId%3D1925596","raw_type":"text"},{"id":"pmh:oai:pub.librecat.org:1925596","is_oa":true,"landing_page_url":"https://pub.uni-bielefeld.de/record/1925596","pdf_url":null,"source":{"id":"https://openalex.org/S4306401671","display_name":"PUB \u2013 Publications at Bielefeld University (Bielefeld University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20121455","host_organization_name":"Bielefeld University","host_organization_lineage":["https://openalex.org/I20121455"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Tscherepanow M. TopoART: A Topology Learning Hierarchical ART Network. In: Diamantaras K, Duch W, Iliadis LS, eds. &lt;em&gt;Artificial Neural Networks (ICANN 2010)&lt;/em&gt;. Lecture Notes in Computer Science, 6354. Berlin: Springer;  2010: 157-167.","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:pub.librecat.org:1925596","is_oa":true,"landing_page_url":"https://pub.uni-bielefeld.de/record/1925596","pdf_url":null,"source":{"id":"https://openalex.org/S4306401671","display_name":"PUB \u2013 Publications at Bielefeld University (Bielefeld University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I20121455","host_organization_name":"Bielefeld University","host_organization_lineage":["https://openalex.org/I20121455"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Tscherepanow M. TopoART: A Topology Learning Hierarchical ART Network. In: Diamantaras K, Duch W, Iliadis LS, eds. &lt;em&gt;Artificial Neural Networks (ICANN 2010)&lt;/em&gt;. Lecture Notes in Computer Science, 6354. Berlin: Springer;  2010: 157-167.","raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W65738273","https://openalex.org/W1485231155","https://openalex.org/W1767354153","https://openalex.org/W1950060225","https://openalex.org/W2012611887","https://openalex.org/W2042203967","https://openalex.org/W2097936475","https://openalex.org/W2099819095","https://openalex.org/W2120250216","https://openalex.org/W2127218421","https://openalex.org/W2134383396","https://openalex.org/W2138754805","https://openalex.org/W2150159007","https://openalex.org/W2159110831","https://openalex.org/W2162647425","https://openalex.org/W2170892502","https://openalex.org/W2796164932","https://openalex.org/W3022351671","https://openalex.org/W4239048948"],"related_works":["https://openalex.org/W3090006299","https://openalex.org/W2160366419","https://openalex.org/W2590565095","https://openalex.org/W2149471286","https://openalex.org/W2112235833","https://openalex.org/W2112751893","https://openalex.org/W821583771","https://openalex.org/W1518241128","https://openalex.org/W2122958142","https://openalex.org/W2482164254"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
