@inbook{507125067bb5457190808824eccd319e,
title = "Machine Learning Based Extractive Text Summarization Using Document Aware and Document Unaware Features",
abstract = "Automatic text summarization isAutomatic text summarization a natural language processing problemNatural language processing useful for education and journalism. Text summarizationLow-resource for low-resource languages is a challenging problem mainly due to a lack of text processing tools and large datasets. This research studies the impactExtractive text summarization of textual features forTextual features extractive text summarization of low-resource languages inLow-resource languages the task of Urdu extractive text summarization. The proposed method extracts textual features thatTextual features better represent the document{\textquoteright}s context helping prediction ofPrediction the summary with greater accuracy. These document-aware features includeDocument-aware features: cosine-position, relativeCosine-position length, ratio of part of speech, ratio of numerical data, TF-ISF. TheTF-ISF support vector regression modelSupport vector regression is trained on extracted document-aware features. The trained model is then used to predict the summary for the original Urdu text in the test document. The evaluation metrics used in this research are ROGUE-1 and ROGUE-2 forROGUE-1 and ROGUE-2 evaluating the summary quality.",
keywords = "Feature extraction, Machine learning, Support vector machine, Text summarizations, low-resource language",
author = "Saleem, \{Muhammad Ammar\} and Junaid Shuja and Humayun, \{Mohammad Ali\} and Ahmed, \{Saad Bin\} and Ahmad, \{Raja Wasim\}",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.",
year = "2024",
doi = "10.1007/978-3-031-67317-7\_9",
language = "English",
series = "Studies in Systems, Decision and Control",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "143--158",
booktitle = "Studies in Systems, Decision and Control",
address = "Germany",
}