{"_buckets": {"deposit": "36d926fa-c989-4abb-a252-272ee7a2744a"}, "_deposit": {"id": "2009974", "owners": [1], "pid": {"revision_id": 0, "type": "depid", "value": "2009974"}, "status": "published"}, "_oai": {"id": "oai:u-ryukyu.repo.nii.ac.jp:02009974", "sets": ["1642838338003", "1642838406845"]}, "author_link": [], "item_1617186331708": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Estimating Age on Twitter Using Self-Training Semi-Supervised SVM", "subitem_1551255648112": "en"}]}, "item_1617186419668": {"attribute_name": "Creator", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Iju, Tatsuyuki", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Endo, Satoshi", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Toma, Naruaki", "creatorNameLang": "en"}]}, {"creatorNames": [{"creatorName": "Akamine, Yuhei", "creatorNameLang": "en"}]}]}, "item_1617186476635": {"attribute_name": "Access Rights", "attribute_value_mlt": [{"subitem_1522299639480": "open access", "subitem_1600958577026": "http://purl.org/coar/access_right/c_abf2"}]}, "item_1617186499011": {"attribute_name": "Rights", "attribute_value_mlt": [{"subitem_1522650717957": "ja", "subitem_1522651041219": "\u00a9 The authors.This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited."}, {"subitem_1522650717957": "en", "subitem_1522650727486": "https://creativecommons.org/licenses/by-nc/4.0/", "subitem_1522651041219": "https://creativecommons.org/licenses/by-nc/4.0/"}]}, "item_1617186609386": {"attribute_name": "Subject", "attribute_value_mlt": [{"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Twitter"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Age"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Semi-supervised learning"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Self-training"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "SVM"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Plat scaling"}]}, "item_1617186626617": {"attribute_name": "Description", "attribute_value_mlt": [{"subitem_description": "The estimation methods for Twitter user\u2019s attributes typically require a vast amount of labeled data. Therefore, an efficient way is to tag the unlabeled data and add it to the set. We applied the self-training SVM as a semi-supervised method for age estimation and introduced Plat scaling as the unlabeled data selection criterion in the self-training process. We show how the performance of the self-training SVM varies when the amount of training data and the selection criterion values are changed.", "subitem_description_type": "Other"}, {"subitem_description": "\u8ad6\u6587", "subitem_description_type": "Other"}]}, "item_1617186643794": {"attribute_name": "Publisher", "attribute_value_mlt": [{"subitem_1522300295150": "en", "subitem_1522300316516": "Atlantis Press"}]}, "item_1617186702042": {"attribute_name": "Language", "attribute_value_mlt": [{"subitem_1551255818386": "eng"}]}, "item_1617186783814": {"attribute_name": "Identifier", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/20.500.12000/42185"}]}, "item_1617186920753": {"attribute_name": "Source Identifier", "attribute_value_mlt": [{"subitem_1522646500366": "ISSN", "subitem_1522646572813": "2352-6386"}]}, "item_1617186941041": {"attribute_name": "Source Title", "attribute_value_mlt": [{"subitem_1522650068558": "en", "subitem_1522650091861": "Journal of Robotics, Networking and Artificial Life"}]}, "item_1617187056579": {"attribute_name": "Bibliographic Information", "attribute_value_mlt": [{"bibliographicIssueNumber": "1", "bibliographicPageEnd": "27", "bibliographicPageStart": "24", "bibliographicVolumeNumber": "3"}]}, "item_1617258105262": {"attribute_name": "Resource Type", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_1617265215918": {"attribute_name": "Version Type", "attribute_value_mlt": [{"subitem_1522305645492": "VoR", "subitem_1600292170262": "http://purl.org/coar/version/c_970fb48d4fbd8a85"}]}, "item_1617353299429": {"attribute_name": "Relation", "attribute_value_mlt": [{"subitem_1522306287251": {"subitem_1522306382014": "DOI", "subitem_1522306436033": "http://dx.doi.org/10.2991/jrnal.2016.3.1.6"}}, {"subitem_1522306287251": {"subitem_1522306382014": "DOI", "subitem_1522306436033": "info:doi/10.2991/jrnal.2016.3.1.6"}}]}, "item_1617605131499": {"attribute_name": "File", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "download_preview_message": "", "file_order": 0, "filename": "25856332.pdf", "future_date_message": "", "is_thumbnail": false, "mimetype": "", "size": 0, "url": {"objectType": "fulltext", "url": "https://u-ryukyu.repo.nii.ac.jp/record/2009974/files/25856332.pdf"}, "version_id": "5114f556-ae8c-4764-9800-14f0e97e502e"}]}, "item_title": "Estimating Age on Twitter Using Self-Training Semi-Supervised SVM", "item_type_id": "15", "owner": "1", "path": ["1642838338003", "1642838406845"], "permalink_uri": "http://hdl.handle.net/20.500.12000/42185", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2018-08-07"}, "publish_date": "2018-08-07", "publish_status": "0", "recid": "2009974", "relation": {}, "relation_version_is_last": true, "title": ["Estimating Age on Twitter Using Self-Training Semi-Supervised SVM"], "weko_shared_id": -1}