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使用远程监督的深网从文本中诱导内隐关系Inducing Implicit Relations from Text using Distantly Supervised Deep Nets |
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| 课程网址: | http://videolectures.net/iswc2018_gliozzo_implicit_relations_dist... |
| 主讲教师: | Alfio Massimiliano Gliozzo |
| 开课单位: | IBM研究 |
| 开课时间: | 2018-10-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | In this paper we present Socrates, a deep learning based solutions for Automated Knowledge Base Population. Socrates does not require hand labelled data for domain adaptation. Instead, it exploits a partially populated knowledge base and a large corpus of text documents to train a deep neural network model. As a result of the training process, the system learns how to identify implicit relations between entities across a highly heterogeneous set of documents from various sources, making it suitable for large-scale knowledge extraction from Web documents. We provide an extensive evaluation of the system across three different benchmarks, showing that we consistently improve over state of the art solutions. Remarkably, Socrates ranked first in both the knowledge base population and attribute validation track at the Semantic Web Challenge at ISWC 2017. |
| 关 键 词: | Socrates; 深度学习的自动知识库; ISWC语义网络挑战赛 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-12-30：cyh |
| 最后编审: | 2023-05-15：cyh |
| 阅读次数: | 26 |