Search Results for author: Dai Quoc Nguyen

Found 28 papers, 17 papers with code

Two-view Graph Neural Networks for Knowledge Graph Completion

no code implementations16 Dec 2021 Vinh Tong, Dai Quoc Nguyen, Dinh Phung, Dat Quoc Nguyen

In this paper, we introduce a novel GNN-based knowledge graph embedding model, named WGE, to capture entity-focused graph structure and relation-focused graph structure.

Knowledge Graph Completion Knowledge Graph Embedding

ReGVD: Revisiting Graph Neural Networks for Vulnerability Detection

1 code implementation14 Oct 2021 Van-Anh Nguyen, Dai Quoc Nguyen, Van Nguyen, Trung Le, Quan Hung Tran, Dinh Phung

Identifying vulnerabilities in the source code is essential to protect the software systems from cyber security attacks.

Graph Embedding Text Classification +1

Automatic Post-Editing for Vietnamese

1 code implementation ALTA 2021 Thanh Vu, Dai Quoc Nguyen

Automatic post-editing (APE) is an important remedy for reducing errors of raw translated texts that are produced by machine translation (MT) systems or software-aided translation.

Automatic Post-Editing Translation

Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction

1 code implementation15 Apr 2021 Dai Quoc Nguyen, Vinh Tong, Dinh Phung, Dat Quoc Nguyen

We introduce a novel embedding model, named NoGE, which aims to integrate co-occurrence among entities and relations into graph neural networks to improve knowledge graph completion (i. e., link prediction).

Knowledge Graph Completion Link Prediction

QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings

1 code implementation26 Sep 2020 Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Phung

We propose a simple yet effective embedding model to learn quaternion embeddings for entities and relations in knowledge graphs.

Knowledge Graph Completion Knowledge Graph Embeddings

Quaternion Graph Neural Networks

1 code implementation12 Aug 2020 Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung

As demonstrated, the Quaternion space, a hyper-complex vector space, provides highly meaningful computations and analogical calculus through Hamilton product compared to the Euclidean and complex vector spaces.

General Classification Graph Classification +4

A Self-Attention Network based Node Embedding Model

1 code implementation22 Jun 2020 Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung

Despite several signs of progress have been made recently, limited research has been conducted for an inductive setting where embeddings are required for newly unseen nodes -- a setting encountered commonly in practical applications of deep learning for graph networks.

General Classification Link Prediction +1

A Vietnamese Text-Based Conversational Agent

no code implementations26 Nov 2019 Dai Quoc Nguyen, Dat Quoc Nguyen, Son Bao Pham

This paper introduces a Vietnamese text-based conversational agent architecture on specific knowledge domain which is integrated in a question answering system.

Question Answering

A Vietnamese Question Answering System

no code implementations26 Nov 2019 Dai Quoc Nguyen, Dat Quoc Nguyen, Son Bao Pham

Question answering systems aim to produce exact answers to users' questions instead of a list of related documents as used by current search engines.

Question Answering

Universal Graph Transformer Self-Attention Networks

1 code implementation26 Sep 2019 Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung

The transformer self-attention network has been extensively used in research domains such as computer vision, image processing, and natural language processing.

Computer Vision General Classification +3

Unsupervised Universal Self-Attention Network for Graph Classification

no code implementations25 Sep 2019 Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung

Thus, U2GAN can address the weaknesses in the existing models in order to produce plausible node embeddings whose sum is the final embedding of the whole graph.

Classification Graph Classification +1

A Relational Memory-based Embedding Model for Triple Classification and Search Personalization

1 code implementation ACL 2020 Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung

Knowledge graph embedding methods often suffer from a limitation of memorizing valid triples to predict new ones for triple classification and search personalization problems.

General Classification Knowledge Graph Embedding +1

A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization

2 code implementations NAACL 2019 Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung

In this paper, we introduce an embedding model, named CapsE, exploring a capsule network to model relationship triples (subject, relation, object).

 Ranked #1 on Link Prediction on FB15k-237 (Evaluation Protocol metric)

Knowledge Graph Completion Link Prediction

A Capsule Network-based Embedding Model for Search Personalization

no code implementations12 Apr 2018 Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Phung

After that, the 3-column matrix is fed into a deep learning architecture to re-rank the search results returned by a basis ranker.

A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network

3 code implementations NAACL 2018 Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung

This 3-column matrix is then fed to a convolution layer where multiple filters are operated on the matrix to generate different feature maps.

 Ranked #1 on Link Prediction on FB15k-237 (Evaluation Protocol metric)

Knowledge Base Completion Link Prediction

From Word Segmentation to POS Tagging for Vietnamese

1 code implementation ALTA 2017 Dat Quoc Nguyen, Thanh Vu, Dai Quoc Nguyen, Mark Dras, Mark Johnson

This paper presents an empirical comparison of two strategies for Vietnamese Part-of-Speech (POS) tagging from unsegmented text: (i) a pipeline strategy where we consider the output of a word segmenter as the input of a POS tagger, and (ii) a joint strategy where we predict a combined segmentation and POS tag for each syllable.

Part-Of-Speech Tagging POS +1

Sequence to Sequence Learning for Event Prediction

1 code implementation IJCNLP 2017 Dai Quoc Nguyen, Dat Quoc Nguyen, Cuong Xuan Chu, Stefan Thater, Manfred Pinkal

This paper presents an approach to the task of predicting an event description from a preceding sentence in a text.

A Mixture Model for Learning Multi-Sense Word Embeddings

no code implementations SEMEVAL 2017 Dai Quoc Nguyen, Dat Quoc Nguyen, Ashutosh Modi, Stefan Thater, Manfred Pinkal

Our model generalizes the previous works in that it allows to induce different weights of different senses of a word.

Word Embeddings

A Robust Transformation-Based Learning Approach Using Ripple Down Rules for Part-of-Speech Tagging

1 code implementation12 Dec 2014 Dat Quoc Nguyen, Dai Quoc Nguyen, Dang Duc Pham, Son Bao Pham

In this paper, we propose a new approach to construct a system of transformation rules for the Part-of-Speech (POS) tagging task.

Part-Of-Speech Tagging POS

Ripple Down Rules for Question Answering

no code implementations12 Dec 2014 Dat Quoc Nguyen, Dai Quoc Nguyen, Son Bao Pham

Recent years have witnessed a new trend of building ontology-based question answering systems.

Question Answering

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