scholarly journals Expanding End-to-End Question Answering on Differentiable Knowledge Graphs with Intersection

2021 ◽  
Author(s):  
Priyanka Sen ◽  
Armin Oliya ◽  
Amir Saffari
Keyword(s):  
Question Answering ◽  
Knowledge Graphs ◽  
End To End

scholarly journals End-to-End Argumentation Knowledge Graph Construction

2020 ◽  
Vol 34 (05) ◽  
pp. 7367-7374
Author(s):  
Khalid Al-Khatib ◽  
Yufang Hou ◽  
Henning Wachsmuth ◽  
Charles Jochim ◽  
Francesca Bonin ◽  
...  
Keyword(s):  
Large Scale ◽  
Question Answering ◽  
Knowledge Graph ◽  
Exploratory Search ◽  
Text Generation ◽  
Fake News ◽  
High Quality ◽  
Web Based ◽  
Knowledge Graphs ◽  
End To End

This paper studies the end-to-end construction of an argumentation knowledge graph that is intended to support argument synthesis, argumentative question answering, or fake news detection, among others. The study is motivated by the proven effectiveness of knowledge graphs for interpretable and controllable text generation and exploratory search. Original in our work is that we propose a model of the knowledge encapsulated in arguments. Based on this model, we build a new corpus that comprises about 16k manual annotations of 4740 claims with instances of the model's elements, and we develop an end-to-end framework that automatically identifies all modeled types of instances. The results of experiments show the potential of the framework for building a web-based argumentation graph that is of high quality and large scale.

scholarly journals End-to-End Entity Resolution and Question Answering Using Differentiable Knowledge Graphs

2021 ◽  
Author(s):  
Amir Saffari ◽  
Armin Oliya ◽  
Priyanka Sen ◽  
Tom Ayoola
Keyword(s):  
Question Answering ◽  
Entity Resolution ◽  
Knowledge Graphs ◽  
End To End

A model for quantitative evaluation of an end-to-end question-answering system

2007 ◽  
Vol 58 (8) ◽  
pp. 1082-1099 ◽  
Author(s):  
Nina Wacholder ◽  
Diane Kelly ◽  
Paul Kantor ◽  
Robert Rittman ◽  
Ying Sun ◽  
...  
Keyword(s):  
Quantitative Evaluation ◽  
Question Answering ◽  
Question Answering System ◽  
End To End

scholarly journals A Survey of Techniques for Constructing Chinese Knowledge Graphs and Their Applications

2018 ◽  
Vol 10 (9) ◽  
pp. 3245 ◽  
Author(s):  
Tianxing Wu ◽  
Guilin Qi ◽  
Cheng Li ◽  
Meng Wang
Keyword(s):  
Artificial Intelligence ◽  
Question Answering ◽  
Knowledge Representation And Reasoning ◽  
Knowledge Graph ◽  
Development History ◽  
One Belt One Road ◽  
History Of ◽  
Knowledge Graphs ◽  
The One ◽  
The Impact

With the continuous development of intelligent technologies, knowledge graph, the backbone of artificial intelligence, has attracted much attention from both academic and industrial communities due to its powerful capability of knowledge representation and reasoning. In recent years, knowledge graph has been widely applied in different kinds of applications, such as semantic search, question answering, knowledge management and so on. Techniques for building Chinese knowledge graphs are also developing rapidly and different Chinese knowledge graphs have been constructed to support various applications. Under the background of the “One Belt One Road (OBOR)” initiative, cooperating with the countries along OBOR on studying knowledge graph techniques and applications will greatly promote the development of artificial intelligence. At the same time, the accumulated experience of China in developing knowledge graphs is also a good reference to develop non-English knowledge graphs. In this paper, we aim to introduce the techniques of constructing Chinese knowledge graphs and their applications, as well as analyse the impact of knowledge graph on OBOR. We first describe the background of OBOR, and then introduce the concept and development history of knowledge graph and typical Chinese knowledge graphs. Afterwards, we present the details of techniques for constructing Chinese knowledge graphs, and demonstrate several applications of Chinese knowledge graphs. Finally, we list some examples to explain the potential impacts of knowledge graph on OBOR.

scholarly journals Question Answering on Scholarly Knowledge Graphs

2020 ◽  
pp. 19-32
Author(s):  
Mohamad Yaser Jaradeh ◽  
Markus Stocker ◽  
Sören Auer
Keyword(s):  
Question Answering ◽  
Knowledge Graphs

BUILD KNOWLEDGE GRAPH FROM HETEROGENEOUS DOCUMENTS

2021 ◽  
Vol 47 (05) ◽  
Author(s):  
NGUYỄN CHÍ HIẾU
Keyword(s):  
Information Retrieval ◽  
Deep Learning ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Question Answering ◽  
Semantic Analysis ◽  
Knowledge Graph ◽  
Question Answering Systems ◽  
Knowledge Graphs

Knowledge Graphs are applied in many fields such as search engines, semantic analysis, and question answering in recent years. However, there are many obstacles for building knowledge graphs as methodologies, data and tools. This paper introduces a novel methodology to build knowledge graph from heterogeneous documents.  We use the methodologies of Natural Language Processing and deep learning to build this graph. The knowledge graph can use in Question answering systems and Information retrieval especially in Computing domain

Improving Question Answering over Knowledge Graphs Using Graph Summarization

2021 ◽  
pp. 489-500 ◽  
Author(s):  
Sirui Li ◽  
Kok Wai Wong ◽  
Chun Che Fung ◽  
Dengya Zhu
Keyword(s):  
Question Answering ◽  
Knowledge Graphs ◽  
Graph Summarization

A short survey on end-to-end simple question answering systems

2020 ◽  
Vol 53 (7) ◽  
pp. 5429-5453
Author(s):  
José Wellington Franco da Silva ◽  
Amanda Drielly Pires Venceslau ◽  
Juliano Efson Sales ◽  
José Gilvan Rodrigues Maia ◽  
Vládia Célia Monteiro Pinheiro ◽  
...  
Keyword(s):  
Question Answering ◽  
Short Survey ◽  
Question Answering Systems ◽  
Simple Question ◽  
End To End
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