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CISQA: Corporate Smart Insights Question Answering System

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Information Integration and Web Intelligence (iiWAS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13635))

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Abstract

The development of semantic information systems is a highly topical issue in various domains, e.g., financial news, which both ordinary users and experts deal with. Until now, queries in natural language on open vocabulary from, e.g., query.wikidata.org were hard to answer. The development of such software offers the possibility to make semantic information systems more effective, efficient, and user-friendly. This paper proposes a semantic knowledge-based question answering system called cisqa. It develops entity linking and relation linking approaches that have been experimentally proven to be superior to the state of the art. cisqa also handles question ambiguity, translates natural language questions into SPARQL-queries, and delivers answers to the user in an appropriate manner.

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Notes

  1. 1.

    https://www.omgwiki.org/API4KB/doku.php.

  2. 2.

    de_core_news_lg-2.3.0 https://spacy.io/models/de#de_core_news_lg.

  3. 3.

    https://spacy.io/.

  4. 4.

    https://www.nltk.org/.

  5. 5.

    https://github.com/jdlauret/SpellChecker.

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Acknowledgment

The research presented in this article is partially funded by the German Federal Ministry of Education and Research (BMBF) through the project PANQURA, grant no. 03COV03F https://qurator.ai/panqura/

Author information

Authors and Affiliations

  1. Data Analytics Center (DANA), Fraunhofer FOKUS, Berlin, Germany

    Le Duyen Sandra Vu, Johannes Jung, Silvio Peikert & Adrian Paschke

  2. Faculty of Information Technology, Middle East University, Amman, Jordan

    Jamal Al Qundus

Authors
  1. Le Duyen Sandra Vu
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  2. Jamal Al Qundus
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  3. Johannes Jung
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  4. Silvio Peikert
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  5. Adrian Paschke
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Corresponding author

Correspondence to Le Duyen Sandra Vu .

Editor information

Editors and Affiliations

  1. La Trobe University, Melbourne, VIC, Australia

    Eric Pardede

  2. Monash University, Melbourne, VIC, Australia

    Pari Delir Haghighi

  3. Johannes Kepler University Linz, Linz, Austria

    Ismail Khalil

  4. Johannes Kepler University Linz, Linz, Austria

    Gabriele Kotsis

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Vu, L.D.S., Qundus, J.A., Jung, J., Peikert, S., Paschke, A. (2022). CISQA: Corporate Smart Insights Question Answering System. In: Pardede, E., Delir Haghighi, P., Khalil, I., Kotsis, G. (eds) Information Integration and Web Intelligence. iiWAS 2022. Lecture Notes in Computer Science, vol 13635. Springer, Cham. https://doi.org/10.1007/978-3-031-21047-1_43

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  • DOI: https://doi.org/10.1007/978-3-031-21047-1_43

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  • Online ISBN: 978-3-031-21047-1

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