MyTextSum : Malay Text Summarization Dataset

Published: 14 September 2021| Version 1 | DOI: 10.17632/r54zh37mc7.1
Suraya Alias


The dataset consists of 100 news articles covering Natural Disaster and Events domains in Malaysia. The news articles are formatted in XML following the DUC 2002 text summarization dataset preparation. The total of 300 human summaries from 3 domains experts are included for summary evaluation. Our MyTextSum model with the application of Pattern-Growth Sentence Compression technique has shown promising results of F-Measure score of 0.5752 agreements when evaluated against human summaries and perform better than the Baselines (uncompressed) model. Citation Reference: Alias, S., Sainin, M. S., & Mohammad, S. K. (2020). Model Peringkasan Teks Ekstraktif Dwibahasa menggunakan Fitur Kekangan Corak Tekstual (Bilingual Extractive Text Summarization Model using Textual Pattern Constraints). GEMA Online® Journal of Language Studies, 20(3). Alias S., Mohammad S.K., Gan K.H., Ping T.T. (2018) MYTextSum: A Malay Text Summarizer Model Using a Constrained Pattern-Growth Sentence Compression Technique. In: Alfred R., Iida H., Ag. Ibrahim A., Lim Y. (eds) Computational Science and Technology. ICCST 2017. Lecture Notes in Electrical Engineering, vol 488. Springer, Singapore.



Universiti Malaysia Sabah


Text Processing, Textual Analysis