Core techniques of question answering systems over knowledge bases: a survey
Abstract The Semantic Web contains an enormous amount of information in the form of
knowledge bases (KB). To make this information available, many question answering (QA) …
knowledge bases (KB). To make this information available, many question answering (QA) …
[HTML][HTML] Neural, symbolic and neural-symbolic reasoning on knowledge graphs
Abstract Knowledge graph reasoning is the fundamental component to support machine
learning applications such as information extraction, information retrieval, and …
learning applications such as information extraction, information retrieval, and …
Improving multi-hop question answering over knowledge graphs using knowledge base embeddings
Abstract Knowledge Graphs (KG) are multi-relational graphs consisting of entities as nodes
and relations among them as typed edges. Goal of the Question Answering over KG (KGQA) …
and relations among them as typed edges. Goal of the Question Answering over KG (KGQA) …
Knowledge graph embedding based question answering
Question answering over knowledge graph (QA-KG) aims to use facts in the knowledge
graph (KG) to answer natural language questions. It helps end users more efficiently and …
graph (KG) to answer natural language questions. It helps end users more efficiently and …
Deep learning for entity matching: A design space exploration
Entity matching (EM) finds data instances that refer to the same real-world entity. In this
paper we examine applying deep learning (DL) to EM, to understand DL's benefits and …
paper we examine applying deep learning (DL) to EM, to understand DL's benefits and …
An end-to-end model for question answering over knowledge base with cross-attention combining global knowledge
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 …
them becomes increasingly important. Question answering over knowledge base (KB-QA) is …
Improved neural relation detection for knowledge base question answering
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 …
Base Question Answering (KBQA). In this paper, we propose a hierarchical recurrent neural …
Neural network-based question answering over knowledge graphs on word and character level
Question Answering (QA) systems over Knowledge Graphs (KG) automatically answer
natural language questions using facts contained in a knowledge graph. Simple questions …
natural language questions using facts contained in a knowledge graph. Simple questions …
Stepwise reasoning for multi-relation question answering over knowledge graph with weak supervision
Knowledge Graph Question Answering aims to automatically answer natural language
questions via well-structured relation information between entities stored in knowledge …
questions via well-structured relation information between entities stored in knowledge …
Complex knowledge base question answering: A survey
Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Early studies mainly focused on answering simple questions over KBs and …
base (KB). Early studies mainly focused on answering simple questions over KBs and …