Name
Title | ||
|---|---|---|
Personal Attributes Extraction in Chinese Text Based on Distant-Supervision and LSTM. |
Abstract | ||
|---|---|---|
In this paper, we proposed a distant-supervision approach to solve the problem of insufficient training corpus for extracting attribute from the unstructured text, by using the wiki infobox information to tag the Wikipedia text to get the training corpus. We consider the extract attribute as the sequence annotation question and use the wiki personal text as the training corpus. The clp-2014 task4 is used as the test corpus to test. The experiment result show that this method can enhance the quality of the attribute extraction. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-981-10-7605-3_84 | ADVANCES IN COMPUTER SCIENCE AND UBIQUITOUS COMPUTING |
Keywords | DocType | Volume |
Deep learning,Entity attribute extraction,LSTM,Sequence padding,NLP,Distant-supervised | Conference | 474 |
ISSN | Citations | PageRank |
1876-1100 | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenxi Yao | 1 | 0 | 0.34 |
| Jin Liu | 2 | 316 | 50.24 |
| Zehuan Cai | 3 | 0 | 0.34 |