66 citations · 172 across the 20 of their papers we have counts for
10 papers · 2 filters
End-to-end neural relation extraction using deep biaffine attention
Dat Quoc Nguyen, Karin Verspoor
We propose a neural network model for joint extraction of named entities and relations between them, without any hand-crafted features. The key contribution of our model is to exte…
A neural joint model for Vietnamese word segmentation, POS tagging and dependency parsing
Dat Quoc Nguyen
We propose the first multi-task learning model for joint Vietnamese word segmentation, part-of-speech (POS) tagging and dependency parsing. In particular, our model extends the BIS…
Improving Topic Models with Latent Feature Word Representations
Dat Quoc Nguyen, Richard Billingsley, Lan Du +1
Probabilistic topic models are widely used to discover latent topics in document collections, while latent feature vector representations of words have been used to obtain high per…
Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition
Zenan Zhai, Dat Quoc Nguyen, Karin Verspoor
We compare the use of LSTM-based and CNN-based character-level word embeddings in BiLSTM-CRF models to approach chemical and disease named entity recognition (NER) tasks. Empirical…
An improved neural network model for joint POS tagging and dependency parsing
Dat Quoc Nguyen, Karin Verspoor
We propose a novel neural network model for joint part-of-speech (POS) tagging and dependency parsing. Our model extends the well-known BIST graph-based dependency parser (Kiperwas…
A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization
Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen +2
In this paper, we introduce an embedding model, named CapsE, exploring a capsule network to model relationship triples (subject, relation, object). Our CapsE represents each triple…