Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2923
Title: Use of Interpretable Evolved Search Query Classifiers for Sinhala Documents
Authors: Haddela, P
Hirsch, L
Brunsdon, T
Gaudoin, J
Keywords: Evolved Search Queries
Genetic Algorithm
Interpretable text classification
Lucene Sinhala Analyzer
Sinhala Document Classification
Issue Date: Jan-2021
Publisher: Springer, Cham
Citation: Haddela, P., Hirsch, L., Brunsdon, T., Gaudoin, J. (2021). Use of Interpretable Evolved Search Query Classifiers for Sinhala Documents. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Proceedings of the Future Technologies Conference (FTC) 2020, Volume 1. FTC 2020. Advances in Intelligent Systems and Computing, vol 1288. Springer, Cham. https://doi.org/10.1007/978-3-030-63128-4_59
Series/Report no.: FTC 2020: Proceedings of the Future Technologies Conference (FTC) 2020,;Volume 1 pp 790–804
Abstract: Document analysis is a well matured yet still active research field, partly as a result of the intricate nature of building computational tools but also due to the inherent problems arising from the variety and complexity of human languages. Breaking down language barriers is vital in enabling access to a number of recent technologies. This paper investigates the application of document classification methods to new Sinhalese datasets. This language is geographically isolated and rich with many of its own unique features. We will examine the interpretability of the classification models with a particular focus on the use of evolved Lucene search queries generated using a Genetic Algorithm (GA) as a method of document classification. We will compare the accuracy and interpretability of these search queries with other popular classifiers. The results are promising and are roughly in line with previous work on English language datasets.
URI: http://rda.sliit.lk/handle/123456789/2923
ISSN: 978-3-030-63127-7
Appears in Collections:Department of Information Technology-Scopes
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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