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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Yulan He Siu Cheung Hui Tho Thanh Quan |
| Copyright Year | 2009 |
| Abstract | Computer-assisted assessment of summary writings is a challenging area which has recently attracted much interest from the research community. This is mainly due to the advances in other areas such as information extraction and natural language processing which have made automatic summary assessment possible. Different techniques such as Latent Semantic Analysis, $n$-gram co-occurrence and BLEUhave been proposed for automatic evaluation of summaries. However, these techniques are unable to achieve good performance. In this paper, we propose an ensemble approach, that integrates two of the most effective summary evaluation techniques, LSA and n-gram co-occurrence, for improving the accuracy of automatic summary assessment. The performance of the proposed ensemble approach has shown that it is able to achieve high accuracy and improve theperformance quite substantially compared with other existingtechniques. |
| Starting Page | 490 |
| Ending Page | 494 |
| File Size | 162408 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424433346 |
| DOI | 10.1109/ICCET.2009.90 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-01-22 |
| Publisher Place | Singapore |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Summary assessment Humans Mathematics Matrix decomposition Data mining Helium Engines Computer-assisted assessment. Computer science N-gram %co-occurrence Writing Cities and towns Natural language processing Latent semantic analysis |
| Content Type | Text |
| Resource Type | Article |
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