{"_buckets": {"deposit": "4a8a43a8-b1e8-4a5c-b418-bd3ae0b5d7ea"}, "_deposit": {"id": "18609", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "18609"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00018609", "sets": ["503"]}, "author_link": ["54085", "54086", "54087", "54088"], "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2011-06", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "2545", "bibliographicPageStart": "2540", "bibliographic_titles": [{"bibliographic_title": "2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)", "bibliographic_titleLang": "en"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "Clustering is one of the most useful methods for understanding similarity among data. However, most conventional clustering methods do not pay sufficient attention to the geometric properties of data. Geometric algebra (GA) is a generalization of complex numbers and quaternions able to describe spatial objects and the relations between them. This paper uses conformal GA (CGA), which is a part of GA, to transform a vector in a real vector space into a vector in a CGA space and presents a proposed new clustering method using conformal vectors. In particular, this paper shows that the proposed method was able to extract the geometric clusters which could not be detected by conventional methods.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10_description_5": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), June 27-30, 2011, Grand Hyatt Taipei, Taipei, Taiwan", "subitem_description_language": "en", "subitem_description_type": "Other"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "DOI", "subitem_identifier_uri": "http://dx.doi.org/10.1109/FUZZY.2011.6007574"}, {"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/20706"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "IEEE", "subitem_publisher_language": "en"}]}, "item_10_relation_11": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_type": "isVersionOf", "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://doi.org/10.1109/FUZZY.2011.6007574", "subitem_relation_type_select": "DOI"}}]}, "item_10_relation_8": {"attribute_name": "ISBN", "attribute_value_mlt": [{"subitem_relation_type": "isPartOf", "subitem_relation_type_id": {"subitem_relation_type_id_text": "978-1-4244-7315-1", "subitem_relation_type_select": "ISBN"}}]}, "item_10_rights_12": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.", "subitem_rights_language": "en"}]}, "item_10_select_15": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_select_item": "author"}]}, "item_10_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "1098-7584", "subitem_source_identifier_type": "PISSN"}]}, "item_1615787544753": {"attribute_name": "出版タイプ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_ab4af688f83e57aa", "subitem_version_type": "AM"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "open access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_abf2"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Minh, Tuan Pham", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "54085", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Tachibana, Kanta", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "54086", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Yoshikawa, Tomohiro", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "54087", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Furuhashi, Takeshi", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "54088", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2018-02-21"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "5_A_Clustering_Method_for_Geometric_Data.pdf", "filesize": [{"value": "639.9 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_note", "mimetype": "application/pdf", "size": 639900.0, "url": {"label": "5_A_Clustering_Method_for_Geometric_Data.pdf", "objectType": "fulltext", "url": "https://nagoya.repo.nii.ac.jp/record/18609/files/5_A_Clustering_Method_for_Geometric_Data.pdf"}, "version_id": "e6bf59f8-bc1e-4d83-841d-ce5107909bd8"}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "conformal geometric algebra", "subitem_subject_scheme": "Other"}, {"subitem_subject": "hyper-sphere", "subitem_subject_scheme": "Other"}, {"subitem_subject": "inner product", "subitem_subject_scheme": "Other"}, {"subitem_subject": "distance", "subitem_subject_scheme": "Other"}, {"subitem_subject": "clustering", "subitem_subject_scheme": "Other"}]}, "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": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "A Clustering Method for Geometric Data based on Approximation using Conformal Geometric Algebra", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "A Clustering Method for Geometric Data based on Approximation using Conformal Geometric Algebra", "subitem_title_language": "en"}]}, "item_type_id": "10", "owner": "1", "path": ["503"], "permalink_uri": "http://hdl.handle.net/2237/20706", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2014-11-06"}, "publish_date": "2014-11-06", "publish_status": "0", "recid": "18609", "relation": {}, "relation_version_is_last": true, "title": ["A Clustering Method for Geometric Data based on Approximation using Conformal Geometric Algebra"], "weko_shared_id": -1}