A survey on complex question answering over knowledge base: Recent advances and challenges

B Fu, Y Qiu, C Tang, Y Li, H Yu, J Sun - arXiv preprint arXiv:2007.13069, 2020 - arxiv.org
Question Answering (QA) over Knowledge Base (KB) aims to automatically answer natural
language questions via well-structured relation information between entities stored in …

Knowledge graph embedding: A survey from the perspective of representation spaces

J Cao, J Fang, Z Meng, S Liang - ACM Computing Surveys, 2024 - dl.acm.org
Knowledge graph embedding (KGE) is an increasingly popular technique that aims to
represent entities and relations of knowledge graphs into low-dimensional semantic spaces …

BERT post-training for review reading comprehension and aspect-based sentiment analysis

H Xu, B Liu, L Shu, PS Yu - arXiv preprint arXiv:1904.02232, 2019 - arxiv.org
Question-answering plays an important role in e-commerce as it allows potential customers
to actively seek crucial information about products or services to help their purchase …

A survey on knowledge graph embedding: Approaches, applications and benchmarks

Y Dai, S Wang, NN Xiong, W Guo - Electronics, 2020 - mdpi.com
A knowledge graph (KG), also known as a knowledge base, is a particular kind of network
structure in which the node indicates entity and the edge represent relation. However, with …

Dependency-driven relation extraction with attentive graph convolutional networks

Y Tian, G Chen, Y Song, X Wan - … of the 59th Annual Meeting of …, 2021 - aclanthology.org
Syntactic information, especially dependency trees, has been widely used by existing
studies to improve relation extraction with better semantic guidance for analyzing the context …

An end-to-end model for question answering over knowledge base with cross-attention combining global knowledge

Y Hao, Y Zhang, K Liu, S He, Z Liu… - Proceedings of the 55th …, 2017 - aclanthology.org
With the rapid growth of knowledge bases (KBs) on the web, how to take full advantage of
them becomes increasingly important. Question answering over knowledge base (KB-QA) is …

Query graph generation for answering multi-hop complex questions from knowledge bases

Y Lan, J Jiang - 2020 - ink.library.smu.edu.sg
Previous work on answering complex questions from knowledge bases usually separately
addresses two types of complexity: questions with constraints and questions with multiple …

Inter-sentence relation extraction with document-level graph convolutional neural network

SK Sahu, F Christopoulou, M Miwa… - arXiv preprint arXiv …, 2019 - arxiv.org
Inter-sentence relation extraction deals with a number of complex semantic relationships in
documents, which require local, non-local, syntactic and semantic dependencies. Existing …

[PDF][PDF] T-rex: A large scale alignment of natural language with knowledge base triples

H Elsahar, P Vougiouklis, A Remaci… - Proceedings of the …, 2018 - aclanthology.org
Alignments between natural language and Knowledge Base (KB) triples are an essential
prerequisite for training machine learning approaches employed in a variety of Natural …

Improved neural relation detection for knowledge base question answering

M Yu, W Yin, KS Hasan, C Santos, B Xiang… - arXiv preprint arXiv …, 2017 - arxiv.org
Relation detection is a core component for many NLP applications including Knowledge
Base Question Answering (KBQA). In this paper, we propose a hierarchical recurrent neural …