| Presentation | 2003/10/30 Boosting with Subtree-based Decision Stumps and Its application to Semi-strucutred Text Classification(Natural Language Understanding and Models of Communication) Taku Kudo, Yuji Matsumoto, |
|---|---|
| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The research focus in text classification has expanded from a simple topic identification to a more challenging task, such as opinion/modality identification. For the latter, the traditional bag-of-word representations are not sufficient, and a richer, more structural representation will be required. Accordingly, learning algorithms must be able to handle such sub-structures observed in text. In this paper, we propose a Boosting algorithm that captures sub-structures embedded in text. The proposal consists of i) decision stumps that use subtree as features and ii) Boosting algorithm in which the subtree-based decision stumps are applied as weak learners. We also discuss a relation between our algorithm and SVM with Tree Kernel. Three experiments on the opinion/modality classification tasks confirm that subtree features are important. Our Boosting algorithm is computationally efficient for classification tasks involving discrete structural features. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Decision Stumps / Boosting / Semi-structured Text Classification / Tree Kernel |
| Paper # | NLC2003-33 |
| Date of Issue |
| Conference Information | |
| Committee | NLC |
|---|---|
| Conference Date | 2003/10/30(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | |
| Vice Chair | |
| Secretary | |
| Assistant | |
| Paper Information | |
| Registration To | Natural Language Understanding and Models of Communication (NLC) |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Boosting with Subtree-based Decision Stumps and Its application to Semi-strucutred Text Classification(Natural Language Understanding and Models of Communication) |
| Sub Title (in English) | |
| Keyword(1) | Decision Stumps |
| Keyword(2) | Boosting |
| Keyword(3) | Semi-structured Text Classification |
| Keyword(4) | Tree Kernel |
| 1st Author's Name | Taku Kudo |
| 1st Author's Affiliation | Graduate School of Information Science, Nara Institute of Science and Technology() |
| 2nd Author's Name | Yuji Matsumoto |
| 2nd Author's Affiliation | Graduate School of Information Science, Nara Institute of Science and Technology |
| Date | 2003/10/30 |
| Paper # | NLC2003-33 |
| Volume (vol) | vol.103 |
| Number (no) | 407 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |