Linking graph entities with multiplicity and provenance
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(Published version)
Date
2019
Authors
Liu, J.
Kwashie, S.
Li, J.
Liu, L.
Bewong, M.
Editors
Cheng, G.
Gunaratna, K.
Wang, A.
Gunaratna, K.
Wang, A.
Advisors
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Conference paper
Citation
CEUR Workshop Proceedings, 2019 / Cheng, G., Gunaratna, K., Wang, A. (ed./s), vol.2446, pp.1-7
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Conference Name
2nd International Workshop on EntitY REtrieval: EYRE’19 (3 Nov 2019 : Beijing, China)
Abstract
Entity linking and resolution is a fundamental database problemwith applications in data integration, data cleansing, information retrieval, knowledge fusion, and knowledge-base population. It is the task of accurately identifying multiple, differing, and possibly contradicting representations of the same real-world entity in data.In this work, we propose an entity linking and resolution system capable of linking entities across different databases and mentioned entities extracted from text data. Our entity linking/resolution solution,called Certus, uses a graph model to represent the profiles of entities. The graph model is versatile, thus, it is capable of handling multiple values for an attribute or a relationship, as well as the provenance descriptions of the values. Provenance descriptions of a value provide the settings of the value, such as validity periods,sources, security requirements, etc. This paper presents the architecture for the entity linking system, the logical, physical, and indexing models used in the system, and the general linking process.Furthermore,we demonstrate the performance of update operations of the physical storage models when the system is implemented in two state-of-the-art database management systems, HBase and Postgres.
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Copyright 2019 the Authors. Use permitted under Creative CommonsLicense Attribution 4.0 International (CC BY 4.0). (https://creativecommons.org/licenses/by/4.0/)