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Abstract

In this demonstration, we present a multi-source hybrid Question Answering (QA) system. Our system consists of four sub-systems: (1) a knowledgebase based QA, (2) an information retrieval based QA, (3) a keyword QA and (4) an information-extraction to construct our own knowledgebase from web texts. With these sub-systems, we can query three types of information sources: curated knowledgebases, automatically constructed knowledgebases and wiki texts.

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Notes

  1. 1.

    https://www.ephyra.info.

  2. 2.

    http://lucene.apache.org/core.

  3. 3.

    http://ticcky.github.io/esalib.

  4. 4.

    “Correct” means the result was reasonable interpretation for the keyword query based on human judgment.

References

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Acknowledgements

This work was supported by ICT R&D program of MSIP/IITP [10044508, Development of Non-Symbolic Approach-based Human-Like Self-Taught Learning Intelligence Technology] and ATC (Advanced Technology Center) Program—‘Development of Conversational Q&A Search Framework Based On Linked Data: Project No. 10048448’.

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Correspondence to Seonyeong Park .

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© 2015 Springer International Publishing Switzerland

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Park, S., Shim, H., Han, S., Kim, B., Lee, G.G. (2015). Multi-Source Hybrid Question Answering System. In: Lee, G., Kim, H., Jeong, M., Kim, JH. (eds) Natural Language Dialog Systems and Intelligent Assistants. Springer, Cham. https://doi.org/10.1007/978-3-319-19291-8_23

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  • DOI: https://doi.org/10.1007/978-3-319-19291-8_23

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19290-1

  • Online ISBN: 978-3-319-19291-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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