{"_buckets": {"deposit": "2368fce6-c10b-4212-98ac-5afe1bcb65a1"}, "_deposit": {"id": "18616", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "18616"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00018616"}, "item_10_biblio_info_6": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2013-06", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "967", "bibliographicPageStart": "962", "bibliographic_titles": [{"bibliographic_title": "2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS)"}]}]}, "item_10_description_4": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "This paper presents a new visualization method based on Higher Order Singular Value Decomposition(HOSVD). This method enables us to select any pairs of vectors from loading matrices, and visualizes features of loading vectors in the form of hi plots of respondents, questions and objects. An experiment is carried out using artificial data. The results shows that the proposed method can visualize the interrelationships between features of selected loading vectors and we can find respondent groups who marked uniquely on particular objects and questions. Some groups are unable to be found by the conventional PCA.", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "DOI", "subitem_identifier_uri": "http://dx.doi.org/10.1109/IFSA-NAFIPS.2013.6608530"}, {"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/20712"}]}, "item_10_publisher_32": {"attribute_name": "\u51fa\u7248\u8005", "attribute_value_mlt": [{"subitem_publisher": "IEEE"}]}, "item_10_rights_12": {"attribute_name": "\u6a29\u5229", "attribute_value_mlt": [{"subitem_rights": "\u00a9 2013 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."}]}, "item_10_select_15": {"attribute_name": "\u8457\u8005\u7248\u30d5\u30e9\u30b0", "attribute_value_mlt": [{"subitem_select_item": "author"}]}, "item_creator": {"attribute_name": "\u8457\u8005", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Masai, Hiroaki"}], "nameIdentifiers": [{"nameIdentifier": "54119", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Yoshikawa, Tomohiro"}], "nameIdentifiers": [{"nameIdentifier": "54120", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Furuhashi, Takeshi"}], "nameIdentifiers": [{"nameIdentifier": "54121", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "\u30d5\u30a1\u30a4\u30eb\u60c5\u5831", "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": "8_Visualization_Method_of_Third-Order_Tensor.pdf", "filesize": [{"value": "686.5 kB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 686500.0, "url": {"label": "8_Visualization_Method_of_Third-Order_Tensor.pdf", "url": "https://nagoya.repo.nii.ac.jp/record/18616/files/8_Visualization_Method_of_Third-Order_Tensor.pdf"}, "version_id": "30389dc3-ef20-4489-8a5a-0bada350b0e0"}]}, "item_language": {"attribute_name": "\u8a00\u8a9e", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "A visualization method of third-order tensor for knowledge extraction from questionnaire data", "item_titles": {"attribute_name": "\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_title": "A visualization method of third-order tensor for knowledge extraction from questionnaire data"}]}, "item_type_id": "10", "owner": "1", "path": ["320/502/503"], "permalink_uri": "http://hdl.handle.net/2237/20712", "pubdate": {"attribute_name": "\u516c\u958b\u65e5", "attribute_name_i18n": "\u516c\u958b\u65e5", "attribute_value": "2014-11-06"}, "publish_date": "2014-11-06", "publish_status": "0", "recid": "18616", "relation": {}, "relation_version_is_last": true, "title": ["A visualization method of third-order tensor for knowledge extraction from questionnaire data"], "weko_shared_id": null}