4.7 Article

Joint entity and relation extraction with position-aware attention and relation embedding

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Artificial Intelligence

Two-level label recovery-based label embedding for multi-label classification with missing labels

Yibin Wang et al.

Summary: Different from single-label learning, multi-label learning with rich semantic information requires label embedding to capture the inherent intelligence of the label space. However, due to the incompleteness of the label space, label data recovery becomes crucial. This paper proposes a two-level label recovery mechanism for multi-label classification, which effectively addresses missing labels in incomplete datasets and improves classification performance by capturing instance and label correlations in the recovered label space.

APPLIED SOFT COMPUTING (2021)

Article Computer Science, Artificial Intelligence

Joint entity and relation extraction model based on rich semantics

Zhiqiang Geng et al.

Summary: The novel method integrating convolutional and recurrent neural networks with attention mechanism achieves joint entity and relation extraction, encoding rich semantics efficiently and taking full advantage of the associated information between entities and relations. Experimental results demonstrate that the proposed method outperforms current pipe-lined and joint approaches in terms of standard F1-score.

NEUROCOMPUTING (2021)

Article Computer Science, Artificial Intelligence

Representation iterative fusion based on heterogeneous graph neural network for joint entity and relation extraction

Kang Zhao et al.

Summary: This paper proposes a relation extraction model RIFRE based on heterogeneous graph neural networks. Through representation iterative fusion, it successfully establishes effective connections between entities and relations, improving the accuracy and efficiency of relation extraction. Empirical results on multiple datasets have demonstrated the superior performance of RIFRE.

KNOWLEDGE-BASED SYSTEMS (2021)

Article Computer Science, Artificial Intelligence

Structural block driven enhanced convolutional neural representation for relation extraction

Dongsheng Wang et al.

APPLIED SOFT COMPUTING (2020)

Proceedings Paper Computer Science, Artificial Intelligence

Adversarial Named Entity Recognition with POS label embedding

Yuxuan Bai et al.

2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) (2020)

Article Computer Science, Information Systems

Boundaries and edges rethinking: An end-to-end neural model for overlapping entity relation extraction

Hao Fei et al.

INFORMATION PROCESSING & MANAGEMENT (2020)

Article Computer Science, Artificial Intelligence

Joint entity recognition and relation extraction as a multi-head selection problem

Giannis Bekoulis et al.

EXPERT SYSTEMS WITH APPLICATIONS (2018)

Article Computer Science, Artificial Intelligence

Joint entity and relation extraction based on a hybrid neural network

Suncong Zheng et al.

NEUROCOMPUTING (2017)

Proceedings Paper Computer Science, Interdisciplinary Applications

Creating Training Corpora for NLG Micro-Planning

Claire Gardent et al.

PROCEEDINGS OF THE 55TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2017), VOL 1 (2017)

Proceedings Paper Computer Science, Interdisciplinary Applications

Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks

Rajarshi Das et al.

PROCEEDINGS OF THE 55TH ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS (ACL 2017), VOL 2 (2017)

Article Computer Science, Artificial Intelligence

Label-Embedding for Image Classification

Zeynep Akata et al.

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2016)

Review Engineering, Electrical & Electronic

A Review of Relational Machine Learning for Knowledge Graphs

Maximilian Nickel et al.

PROCEEDINGS OF THE IEEE (2016)

Article Engineering, Electrical & Electronic

Deep Neural Networks for Acoustic Modeling in Speech Recognition

Geoffrey Hinton et al.

IEEE SIGNAL PROCESSING MAGAZINE (2012)