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Generating Quiz Questions from Knowledge Graphs

Authors:

Dominic Seyler,

Mohamed Yahya,

Klaus BerberichAuthors Info & Claims

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

Pages 113 - 114

https://doi.org/10.1145/2740908.2742722

Published: 18 May 2015 Publication History

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Abstract

We propose an approach to generate natural language questions from knowledge graphs such as DBpedia and YAGO. We stage this in the setting of a quiz game. Our approach, though, is general enough to be applicable in other settings. Given a topic of interest (e.g., Soccer) and a difficulty (e.g., hard), our approach selects a query answer, generates a SPARQL query having the answer as its sole result, before verbalizing the question.

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J. Hoffart et al.: YAGO2: A spatially and temporally enhanced knowledge base from wikipedia. AI, 2013.

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M. Yahya et al. Robust Question Answering over the Web of Linked Data. CIKM 2013

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Cited By

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Chen YWu LZaki M(2024)Toward Subgraph-Guided Knowledge Graph Question Generation With Graph Neural NetworksIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2023.326451935:9(12706-12717)Online publication date: Sep-2024
https://doi.org/10.1109/TNNLS.2023.3264519
Dong CShen YLin SLin ZDeng Y(2024)A Unified Framework for Contextual and Factoid Question GenerationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.328018236:1(21-34)Online publication date: Jan-2024
https://doi.org/10.1109/TKDE.2023.3280182
Suissa OZhitomirsky-Geffet MElmalech A(2022)Question answering with deep neural networks for semi-structured heterogeneous genealogical knowledge graphsSemantic Web10.3233/SW-22292514:2(209-237)Online publication date: 15-Dec-2022
https://doi.org/10.3233/SW-222925
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Index Terms

Generating Quiz Questions from Knowledge Graphs
1. Information systems

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Knowledge Questions from Knowledge Graphs
ICTIR '17: Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval

We address the problem of automatically generating quiz-style knowledge questions from a knowledge graph such as DBpedia. Questions of this kind have ample applications, for instance, to educate users about or to evaluate their knowledge in a specific ...
Querying Knowledge Graphs by Example Entity Tuples
We witness an unprecedented proliferation of knowledge graphs that record millions of entities and their relationships. While knowledge graphs are structure-flexible and content-rich, they are difficult to use. The challenge lies in the gap between their ...
Question Answering over Knowledge Graphs with Query Path Generation
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Abstract
Knowledge graphs have been applied in question answering. Many researchers have proposed methods based on query graph generation, but there are some defects such as high cost of query graph generation and large search scope of knowledge graphs. ...

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Published In

WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web

May 2015

1602 pages

ISBN:9781450334730

DOI:10.1145/2740908

General Chairs:
Aldo Gangemi
National Research Council, Italy & Paris 13 University-CNRS, France
,
Stefano Leonardi
Sapienza University of Rome, Italy
,
Alessandro Panconesi
Sapienza University of Rome, Italy

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

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Published: 18 May 2015

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WWW '15

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IW3C2

WWW '15: 24th International World Wide Web Conference

May 18 - 22, 2015

Florence, Italy

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Chen YWu LZaki M(2024)Toward Subgraph-Guided Knowledge Graph Question Generation With Graph Neural NetworksIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2023.326451935:9(12706-12717)Online publication date: Sep-2024
https://doi.org/10.1109/TNNLS.2023.3264519
Dong CShen YLin SLin ZDeng Y(2024)A Unified Framework for Contextual and Factoid Question GenerationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.328018236:1(21-34)Online publication date: Jan-2024
https://doi.org/10.1109/TKDE.2023.3280182
Suissa OZhitomirsky-Geffet MElmalech A(2022)Question answering with deep neural networks for semi-structured heterogeneous genealogical knowledge graphsSemantic Web10.3233/SW-22292514:2(209-237)Online publication date: 15-Dec-2022
https://doi.org/10.3233/SW-222925
Xiong GBao JZhao WWu YHe XAl Hasan MXiong L(2022)AutoQGSProceedings of the 31st ACM International Conference on Information & Knowledge Management10.1145/3511808.3557246(2250-2259)Online publication date: 17-Oct-2022
https://dl.acm.org/doi/10.1145/3511808.3557246
Hu YYang HZhou GHuang J(2022)Generating Factoid Questions with Question Type Enhanced Representation and Attention-based Copy MechanismACM Transactions on Asian and Low-Resource Language Information Processing10.1145/347455521:2(1-18)Online publication date: 28-Jan-2022
https://dl.acm.org/doi/10.1145/3474555
Wang Z(2022)Generating Complex Questions from Knowledge Graphs with Query Graphs2022 IEEE 10th International Conference on Information, Communication and Networks (ICICN)10.1109/ICICN56848.2022.10006514(606-613)Online publication date: 23-Aug-2022
https://doi.org/10.1109/ICICN56848.2022.10006514
Fettach YGhogho MBenatallah B(2022)Knowledge Graphs in Education and Employability: A Survey on Applications and TechniquesIEEE Access10.1109/ACCESS.2022.319406310(80174-80183)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3194063
Wittig APerevalov ABoth A(2022)Towards Bridging the Gap Between Knowledge Graphs and ChatbotsWeb Engineering10.1007/978-3-031-09917-5_21(315-322)Online publication date: 1-Jul-2022
https://doi.org/10.1007/978-3-031-09917-5_21
Venugopal VKumar P(2020)Difficulty-level modeling of ontology-based factual questionsSemantic Web10.3233/SW-20038111:6(1023-1036)Online publication date: 1-Jan-2020
https://dl.acm.org/doi/10.3233/SW-200381
Kumar VHua YRamakrishnan GQi GGao LLi Y(2019)Difficulty-Controllable Multi-hop Question Generation from Knowledge GraphsThe Semantic Web – ISWC 201910.1007/978-3-030-30793-6_22(382-398)Online publication date: 17-Oct-2019
https://doi.org/10.1007/978-3-030-30793-6_22
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Knowledge Questions from Knowledge Graphs

Querying Knowledge Graphs by Example Entity Tuples

Question Answering over Knowledge Graphs with Query Path Generation

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