研究者総覧
論文
- タイトル
- タイトル（英）
- Monotone Increasing Binary Similarity and Its Application to Automatic Document-Acquisition of a Category
- 参照URL
- https://researchmap.jp/mikami_yoshiki/published_papers/16620938
- 著者
- 著者（英）
- Izumi Suzuki,Yoshiki Mikami,Ario Ohsato
- 担当区分
- 概要
- 概要（英）
- A technique that acquires documents in the same category with a given short text is introduced. Regarding the given text as a training document, the system marks up the most similar document, or sufficiently similar documents, from among the document domain (or entire Web). The system then adds the marked documents to the training set to learn the set, and this process is repeated until no more documents are marked. Setting a monotone increasing property to the similarity as it learns enables the system to 1) detect the correct timing so that no more documents remain to be marked and to 2) decide the threshold value that the classifier uses. In addition, under the condition that the normalization process is limited to what term weights are divided by a p-norm of the weights, the linear classifier in which training documents are indexed in a binary manner is the only instance that satisfies the monotone increasing property. The feasibility of the proposed technique was confirmed through an examination of binary similarity and using English and German documents randomly selected from the Web.
- 出版者・発行元
- 出版者・発行元（英）
- IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
- 誌名
- 誌名（英）
- IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
- 巻
- E91D
- 号
- 11
- 開始ページ
- 2545
- 終了ページ
- 2551
- 出版年月
- 2008年11月
- 査読の有無
- 査読有り
- 招待の有無
- 掲載種別
- 研究論文（学術雑誌）
- ISSN
- 1745-1361
- DOI URL
- https://doi.org/10.1093/ietisy/e91-d.11.2545
- 共同研究・競争的資金等の研究課題
研究者
三上 喜貴
(ミカミ ヨシキ)