An Ensemble Keyword Extraction Model for News Texts with Statistical and Graphical Features
Abibullayeva A. Kılıç H. Cetin A.
1 July 2024World Scientific
International Journal of Software Engineering and Knowledge Engineering
2024#34Issue 71047 - 1061 pp.
Keyword extraction is an essential tool for many text mining applications such as automatic indexing, summarizing, classification, clustering and automatic filtering. Automated keyword extraction is essential as the daily text data to be reached and processed have increased tremendously over the Internet, e.g. millions of news articles are published daily online. In this paper, a novel ensemble model for automatic extraction of keywords from news articles is proposed. The proposed model handles keyword extraction as a sequence labeling task. Two sub-modules representing the statistical and graphical features by their calculated scores for each input token were combined in the token classification module. The Ensemble Token Classification module was trained and tested separately with the ensemble algorithms Random Forest, XgBoost, Decision Tree and Voting Classification. For training, we collected two news datasets from Kazakh and Russian news sites published in Cyrillic alphabet. We also collected an Arabic news dataset, ArabianNews. The performance of the model was also compared with the widely used 500N-KPCrowd dataset in the literature, which consists of English news content in Latin alphabet. The proposed model achieved the best performance with an F1-score of 0.71 and 0.86 on the 500N-KPCrowd and Russian datasets, respectively. We attained the best F1-score (0.97) with the KazakhNews and ArabianNews datasets.
ensemble classification , graph-based , Keyword extraction , statistical
Text of the article Перейти на текст статьи
Computer Engineering Department, Faculty of Engineering, Akhmet Yassawi University, Turkistan, Kazakhstan
Computer Engineering Department, Faculty of Technology, Gazi University, Ankara, 06500, Turkey
Computer Engineering Department
Computer Engineering Department
10 лет помогаем публиковать статьи Международный издатель
Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026