Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/4263
Title: Türkçe Haber Metinleri için Makine Öğrenmesi Temelli Özetleme
Other Titles: Machine Learning Based Text Summarization for Turkish News
Authors: Kartal, Yavuz Selim
Kutlu, Mücahid
Keywords: Text Summarization
Machine Learning
Issue Date: Sep-2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Kartal, Y. S., & Kutlu, M. (2020, October). Machine Learning Based Text Summarization for Turkish News. In 2020 28th Signal Processing and Communications Applications Conference (SIU) (pp. 1-4). IEEE.
Abstract: In this paper, we propose an automatic text summarization model for Turkish news articles using machine learning models. Our proposed model uses sentence position, speech expression, presence of named entities and statements, term frequency and title similarity as features. We construct and share a new dataset for Turkish text summarization. In our experiments, we show that all our features we use have a positive impact on the performance of the system. In addition, we show that our model outperforms the latent semantic analysis based baseline method.
URI: https://hdl.handle.net/20.500.11851/4263
https://ieeexplore.ieee.org/document/9302096
ISBN: 978-172817206-4
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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