Title: Query optimisation with weighted fish school search in ontological database with application of bioinformatics

Authors: R. Jaya; C.S. Pillai; R. Jagadeesh Kannan

Addresses: Visvesvaraya Technological University, Karnataka, India ' Department of Computer Science and Engineering, ACS College of Engineering, Bangalore, Karnataka, India ' School of Computing Science and Engineering, VIT University Chennai Campus, Chennai, India

Abstract: Making queries from large ontological database has a severe problem of generating query plans as it is made in form of left tree search form. This restricts the querying for composite applications and speed of acquiring query results. In such a scenario the most prominent approach is to optimise the indexing of graph nodes in ontological database and many evolutionary and particle of swarm optimisation (PSO)-based approach had already been attempted. However, loss of diversity and unanticipated convergence causes the solution to remain sub-optimal. In this study we present a weighted fish school searching-based query optimisation technique owing to its scalability and self control functioning with the application of bioinformatics. It creates probabilistic logic-based weight system for the fish school search in a hierarchical tree form which results in increased accuracy when put in comparison with standard PSO-based methods and its other variants.

Keywords: optimisation; semantic data; particle of swarm optimisation; PSO.

DOI: 10.1504/IJMEI.2020.10022851

International Journal of Medical Engineering and Informatics, 2020 Vol.12 No.6, pp.568 - 580

Received: 28 Aug 2017
Accepted: 18 Jun 2018

Published online: 06 Nov 2020 *

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