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| Content Provider | ACM Digital Library |
|---|---|
| Author | Onsuwan, Chutamanee Theeramunkong, Thanaruk Ketui, Nongnuch |
| Copyright Year | 2015 |
| Abstract | Due to lack of a word/phrase/sentence boundary, summarization of Thai multiple documents has several challenges in unit segmentation, unit selection, duplication elimination, and evaluation dataset construction. In this article, we introduce Thai Elementary Discourse Units (TEDUs) and their derivatives, called Combined TEDUs (CTEDUs), and then present our three-stage method of Thai multi-document summarization, that is, unit segmentation, unit-graph formulation, and unit selection and summary generation. To examine performance of our proposed method, a number of experiments are conducted using 50 sets of Thai news articles with their manually constructed reference summaries. Based on measures of ROUGE-1, ROUGE-2, and ROUGE-SU4, the experimental results show that: (1) the TEDU-based summarization outperforms paragraph-based summarization; (2) our proposed graph-based TEDU weighting with importance-based selection achieves the best performance; and (3) unit duplication consideration and weight recalculation help improve summary quality. |
| Starting Page | 1 |
| Ending Page | 26 |
| Page Count | 26 |
| File Format | |
| ISSN | 23754699 |
| e-ISSN | 23754702 |
| DOI | 10.1145/2641567 |
| Volume Number | 14 |
| Issue Number | 1 |
| Journal | ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-01-30 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | EDU-based approach Multi-document summarization Thai text summarization Unit selection |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Science |
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