Data Fusion in Question Answering Systems over Multiple-Knowledge Bases

DOI

10.2991/asum.k.210827.031How to use a DOI?

Keywords

Data fusion, RDF, Equivalent property, Trustworthiness

Abstract

The additional ability to span over multiple Knowledge Bases would further increase the usefulness and potentially comprehensiveness of the system’s responses. Multiple different Knowledge Bases, as much as they can complement each other regarding the lack of specific information, quite often contain inconsistent pieces of information. This makes data fusing a difficult task. In this paper, we propose a methodology for fusing data retrieved from multiple different Knowledge Bases that use different naming schemas. It also contains a procedure for determining degrees of trustworthiness in the Bases. These degrees are included in the data fusion process.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Nhuan D. To
AU  - Marek Z. Reformat
PY  - 2021
DA  - 2021/08/30
TI  - Data Fusion in Question Answering Systems over Multiple-Knowledge Bases
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 227
EP  - 234
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.031
DO  - 10.2991/asum.k.210827.031
ID  - To2021
ER  -