Tibetan entity relation extraction based on multi-level attention fusion mechanism
Compared with Chinese and English, the training corpus of Tibetan entity relation is smaller, so it is difficult to obtain higher accuracy based on traditional supervised learning methods.And there exists the problem of wrong labels in distant supervision for relation extraction.To solve these probl...
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| Format: | Article |
| Language: | zho |
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POSTS&TELECOM PRESS Co., LTD
2021-12-01
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| Series: | 智能科学与技术学报 |
| Subjects: | |
| Online Access: | http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202146 |
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| author | Like WANG Yuan SUN Sisi LIU |
| author_facet | Like WANG Yuan SUN Sisi LIU |
| author_sort | Like WANG |
| collection | DOAJ |
| description | Compared with Chinese and English, the training corpus of Tibetan entity relation is smaller, so it is difficult to obtain higher accuracy based on traditional supervised learning methods.And there exists the problem of wrong labels in distant supervision for relation extraction.To solve these problems, the distant supervision method was used to construct the data set of Tibetan entity relation extraction through aligning the knowledge base with texts, which could alleviate the problem of lacking of large-scale corpus in Tibetan.And a Tibetan entity relation extraction model based on multi-level attention fusion mechanism was proposed.The self-attention was added to extract internal features of words in word level.The selective attention mechanism could assign weights of each instance, so as to make full use of informative sentences and reduce weights of noisy instances.Meanwhile, a joint score function was introduced to correct wrong labels, and neural network was combined with support vector machine to extract relations.Experimental results show that the proposed model can effectively improve the accuracy of Tibetan entity relation extraction, and is better than the baseline. |
| format | Article |
| id | doaj-art-103212d2e5ab4e079dd615abede35720 |
| institution | OA Journals |
| issn | 2096-6652 |
| language | zho |
| publishDate | 2021-12-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 智能科学与技术学报 |
| spelling | doaj-art-103212d2e5ab4e079dd615abede357202025-08-20T02:13:41ZzhoPOSTS&TELECOM PRESS Co., LTD智能科学与技术学报2096-66522021-12-01346647359641617Tibetan entity relation extraction based on multi-level attention fusion mechanismLike WANGYuan SUNSisi LIUCompared with Chinese and English, the training corpus of Tibetan entity relation is smaller, so it is difficult to obtain higher accuracy based on traditional supervised learning methods.And there exists the problem of wrong labels in distant supervision for relation extraction.To solve these problems, the distant supervision method was used to construct the data set of Tibetan entity relation extraction through aligning the knowledge base with texts, which could alleviate the problem of lacking of large-scale corpus in Tibetan.And a Tibetan entity relation extraction model based on multi-level attention fusion mechanism was proposed.The self-attention was added to extract internal features of words in word level.The selective attention mechanism could assign weights of each instance, so as to make full use of informative sentences and reduce weights of noisy instances.Meanwhile, a joint score function was introduced to correct wrong labels, and neural network was combined with support vector machine to extract relations.Experimental results show that the proposed model can effectively improve the accuracy of Tibetan entity relation extraction, and is better than the baseline.http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202146Tibetan;entity relation extraction;multi-level attention fusion mechanism;support vector machine |
| spellingShingle | Like WANG Yuan SUN Sisi LIU Tibetan entity relation extraction based on multi-level attention fusion mechanism 智能科学与技术学报 Tibetan;entity relation extraction;multi-level attention fusion mechanism;support vector machine |
| title | Tibetan entity relation extraction based on multi-level attention fusion mechanism |
| title_full | Tibetan entity relation extraction based on multi-level attention fusion mechanism |
| title_fullStr | Tibetan entity relation extraction based on multi-level attention fusion mechanism |
| title_full_unstemmed | Tibetan entity relation extraction based on multi-level attention fusion mechanism |
| title_short | Tibetan entity relation extraction based on multi-level attention fusion mechanism |
| title_sort | tibetan entity relation extraction based on multi level attention fusion mechanism |
| topic | Tibetan;entity relation extraction;multi-level attention fusion mechanism;support vector machine |
| url | http://www.cjist.com.cn/thesisDetails#10.11959/j.issn.2096-6652.202146 |
| work_keys_str_mv | AT likewang tibetanentityrelationextractionbasedonmultilevelattentionfusionmechanism AT yuansun tibetanentityrelationextractionbasedonmultilevelattentionfusionmechanism AT sisiliu tibetanentityrelationextractionbasedonmultilevelattentionfusionmechanism |