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CUTE: Querying Knowledge Graphs by Tabular Examples

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Web and Big Data (APWeb-WAIM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10987))

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Abstract

Knowledge graphs and the query language SPARQL have opened up the possibility of retrieving information, acquiring knowledge and building applications over large linked data. However, due to the unfamiliarity with both SPARQL and the datasets, users always struggle to write well-expressed queries. To increase the usability of knowledge graphs, we develop a query-by-example system CUTE, which supports complex query intent. CUTE takes tabular examples as input, and returns high-quality results via continuous user interaction.

T. Li—Equal contribution with the first author.

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Notes

  1. 1.

    https://linkeddata1.calcul.u-psud.fr/sparql.

  2. 2.

    https://dbpedia.org/sparql.

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Acknowledgements

This research is funded by China Postdoctoral Science Foundation (No. 2017M610020), National Natural Science Foundation of China (No. 61702015), Shenzhen Gov Research Project (No. CYJ20151014093505032).

Author information

Authors and Affiliations

  1. School of EECS, Key Lab of HCST (MOE), Peking University, Beijing, China

    Zichen Wang, Tian Li, Yingxia Shao & Bin Cui

  2. ECE, Shenzhen Graduate School, Peking University, Shenzhen, China

    Bin Cui

Authors
  1. Zichen Wang
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  2. Tian Li
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  3. Yingxia Shao
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  4. Bin Cui
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Corresponding author

Correspondence to Yingxia Shao .

Editor information

Editors and Affiliations

  1. South China University of Technology, Guangzhou, China

    Yi Cai

  2. Nagoya University, Nagoya, Japan

    Yoshiharu Ishikawa

  3. Hong Kong Baptist University, Kowloon Tong, Hong Kong, China

    Jianliang Xu

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Cite this paper

Wang, Z., Li, T., Shao, Y., Cui, B. (2018). CUTE: Querying Knowledge Graphs by Tabular Examples. In: Cai, Y., Ishikawa, Y., Xu, J. (eds) Web and Big Data. APWeb-WAIM 2018. Lecture Notes in Computer Science(), vol 10987. Springer, Cham. https://doi.org/10.1007/978-3-319-96890-2_39

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  • DOI: https://doi.org/10.1007/978-3-319-96890-2_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96889-6

  • Online ISBN: 978-3-319-96890-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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