| 大会名称 |
|---|
| 2016年 総合大会 |
| 大会コ－ド |
| 2016G |
| 開催年 |
| 2016 |
| 発行日 |
| 2016/3/1 |
| セッション番号 |
| D-5 |
| セッション名 |
| 言語理解とコミュニケーション |
| 講演日 |
| 2016/3/15 |
| 講演場所(会議室等) |
| センター2号館 3F 2302 |
| 講演番号 |
| D-5-9 |
| タイトル |
| Authorship Identification focused on Sentence and Document Based Features |
| 著者名 |
| ◎Shofi Nur Fathiya, Masaki Aono, |
| キーワード |
| feature, text mining |
| 抄録 |
| In this paper, we describe a method for author identification focused on sentence based features. For instance, we propose features such as the number of words per sentence in one document and the number of commas per sentence in one document. To evaluate the effectiveness of our proposed features, we demonstrate through experiments using RCV1 (Reuters Corpus Volume 1) subset. |
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