{"created":"2023-06-20T12:56:38.727685+00:00","id":683,"links":{},"metadata":{"_buckets":{"deposit":"21e2531f-fd6d-4fe3-96bb-c44b9661bb3f"},"_deposit":{"created_by":2,"id":"683","owners":[2],"pid":{"revision_id":0,"type":"depid","value":"683"},"status":"published"},"_oai":{"id":"oai:fun.repo.nii.ac.jp:00000683","sets":["22:33","25:26:37"]},"author_link":["1147","18"],"item_9_biblio_info_5":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"1994-11","bibliographicIssueDateType":"Issued"},"bibliographic_titles":[{"bibliographic_title":"Proceedings of the Artificial Neural Networks In Engineering"}]}]},"item_9_description_3":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"This study focuses on knowledge representa-tion as based on the distributed representation by the Boltzmann machine. In this type of framework, concepts are represented uniformly without any information on their structural relationship. To utilize such information, this study explores how the hierarchical structure of concepts can be extracted from the weights of a trained network. The hierarchy dealt with here is a taxonomical one which is represented by a tree of microfeatures of a concept. Here, the tree is extracted by using various kinds of local criteria relating to weight distribution. To satisfy them simultaneously, a Genetic Algorithm is adopted.","subitem_description_type":"Abstract"}]},"item_9_select_10":{"attribute_name":"単著共著","attribute_value_mlt":[{"subitem_select_item":"共著/joint"}]},"item_9_select_8":{"attribute_name":"査読有無","attribute_value_mlt":[{"subitem_select_item":"あり/yes"}]},"item_9_select_9":{"attribute_name":"研究業績種別","attribute_value_mlt":[{"subitem_select_item":"国際会議/International Conference"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"","affiliationNameIdentifierScheme":"ISNI","affiliationNameIdentifierURI":"http://www.isni.org/isni/"}],"affiliationNames":[{"affiliationName":"","affiliationNameLang":"ja"}]}],"creatorNames":[{"creatorName":"奥野, 拓","creatorNameLang":"ja"}],"familyNames":[{"familyName":"奥野","familyNameLang":"ja"}],"givenNames":[{"givenName":"拓","givenNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"18","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"30360936","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://kaken.nii.ac.jp/ja/search/?qm=30360936"}]},{"creatorNames":[{"creatorName":"Kakazu, Yukinori"}],"nameIdentifiers":[{"nameIdentifier":"1147","nameIdentifierScheme":"WEKO"}]}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"conference paper","resourceuri":"http://purl.org/coar/resource_type/c_5794"}]},"item_title":"Extraction of Embedded Hierarchical Structure of Knowledge from Trained Boltzmann Machine by Genetic  algorithm","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Extraction of Embedded Hierarchical Structure of Knowledge from Trained Boltzmann Machine by Genetic  algorithm"}]},"item_type_id":"9","owner":"2","path":["33","37"],"pubdate":{"attribute_name":"公開日","attribute_value":"2011-04-19"},"publish_date":"2011-04-19","publish_status":"0","recid":"683","relation_version_is_last":true,"title":["Extraction of Embedded Hierarchical Structure of Knowledge from Trained Boltzmann Machine by Genetic  algorithm"],"weko_creator_id":"2","weko_shared_id":-1},"updated":"2025-02-07T02:50:55.029703+00:00"}