{"created":"2022-01-31T07:55:19.926115+00:00","id":2009974,"links":{},"metadata":{"_buckets":{"deposit":"29405c4b-c6e2-4a57-aa3c-f0219a71a867"},"_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":["1642838163960:1642838338003","1642838403551:1642838406845"]},"author_link":[],"control_number":"2009974","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":"© 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’s 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":"論文","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":"EISSN","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":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2016-06","bibliographicIssueDateType":"Issued"},"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":"https://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","filename":"25856332.pdf","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://u-ryukyu.repo.nii.ac.jp/record/2009974/files/25856332.pdf"},"version_id":"c57310d3-1091-4d55-98e9-ddf8d2ee945d"}]},"item_title":"Estimating Age on Twitter Using Self-Training Semi-Supervised SVM","item_type_id":"15","owner":"1","path":["1642838338003","1642838406845"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2018-08-07"},"publish_date":"2018-08-07","publish_status":"0","recid":"2009974","relation_version_is_last":true,"title":["Estimating Age on Twitter Using Self-Training Semi-Supervised SVM"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-08-03T05:36:23.528160+00:00"}