{"_buckets": {"deposit": "e4b1def1-1080-490c-8b57-9c61ee266a8e"}, "_deposit": {"id": "8649", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "8649"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00008649"}, "item_18_biblio_info_6": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2005-12", "bibliographicIssueDateType": "Issued"}, "bibliographicPageEnd": "114", "bibliographicPageStart": "114", "bibliographic_titles": [{"bibliographic_title": "Third Symposium on \"Intelligent Media Integration for Social Information Infrastructure\" December 6, 2005"}]}]}, "item_18_description_4": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "Although many cognitive models have successfully simulated the results of controlled psychological experiments, few researchers have attempted to apply their models to complex, realistic phenomena. In this study, MAC/FAC(\"many are called, but few are chosen\"), which models two stages of analogical reasoning [Forbus, 1995], was appled to our experimental data. In our experiment, subjects were presented a cue story (Figure 1) and asked to retrieve cases learned from everyday life. Next they rated the goodness as an analogy of each retrieved case. For each retrieved case, we used the algorithms of the MAC/FAC to compute two kinds of similarity scores: CV ectors and SESs. As a result, the computed content vectors explained the overall retrieval of cases well, whereas the structural evaluation scores had a strong relation to the rated scores (Figure 2). These results support the MAC/FAC\u0027s theoretical assumption-different similarities are involved in the two stages of analogical reasoning.", "subitem_description_type": "Abstract"}]}, "item_18_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/10400"}]}, "item_18_publisher_32": {"attribute_name": "\u51fa\u7248\u8005", "attribute_value_mlt": [{"subitem_publisher": "INTELLIGENT MEDIA INTEGRATION  NAGOYA UNIVERSITY / COE"}]}, "item_18_select_15": {"attribute_name": "\u8457\u8005\u7248\u30d5\u30e9\u30b0", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_18_text_14": {"attribute_name": "\u30d5\u30a9\u30fc\u30de\u30c3\u30c8", "attribute_value_mlt": [{"subitem_text_value": "application/pdf"}]}, "item_creator": {"attribute_name": "\u8457\u8005", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Morita, Junya"}], "nameIdentifiers": [{"nameIdentifier": "24344", "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": "2018-02-19"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "p114_Morita_Junya.pdf", "filesize": [{"value": "1.9 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 1900000.0, "url": {"label": "p114_Morita_Junya.pdf", "url": "https://nagoya.repo.nii.ac.jp/record/8649/files/p114_Morita_Junya.pdf"}, "version_id": "8c53412d-3d56-412f-a71a-920882cbdae9"}]}, "item_keyword": {"attribute_name": "\u30ad\u30fc\u30ef\u30fc\u30c9", "attribute_value_mlt": [{"subitem_subject": "cognitive science", "subitem_subject_scheme": "Other"}, {"subitem_subject": "open-ended data", "subitem_subject_scheme": "Other"}, {"subitem_subject": "cognitive modeling", "subitem_subject_scheme": "Other"}, {"subitem_subject": "analogical reasoning", "subitem_subject_scheme": "Other"}]}, "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": "conference paper", "resourceuri": "http://purl.org/coar/resource_type/c_5794"}]}, "item_title": "A Cognitive Analysis Model for Complex Open-ended Analogical Retrieval", "item_titles": {"attribute_name": "\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_title": "A Cognitive Analysis Model for Complex Open-ended Analogical Retrieval", "subitem_title_language": "en"}]}, "item_type_id": "18", "owner": "1", "path": ["312/1037/1038"], "permalink_uri": "http://hdl.handle.net/2237/10400", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2008-08-19"}, "publish_date": "2008-08-19", "publish_status": "0", "recid": "8649", "relation": {}, "relation_version_is_last": true, "title": ["A Cognitive Analysis Model for Complex Open-ended Analogical Retrieval"], "weko_shared_id": null}