Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/3782
Title: ACADEMIC TEXT CLUSTERING USING NATURAL LANGUAGE PROCESSING
Authors: Taşkıran, Fatma
Kaya, Ersin
Keywords: Natural Language Processing
Machine Learning
Text Representation
Abstract: Accessing data is very easy nowadays. However, to use these data in an efficient way, it is necessary to get the right information from them. Categorizing these data in order to reach the needed information in a short time provides great convenience. All the more, while doing research in the academic field, text-based data such as articles, papers, or thesis studies are generally used. Natural language processing and machine learning methods are used to get the right information we need from these text-based data. In this study, abstracts of academic papers are clustered. Text data from academic paper abstracts are preprocessed using natural language processing techniques. A vectorized word representation extracted from preprocessed data with Word2Vec and BERT word embeddings and representations are clustered with four clustering algorithms.
URI: https://doi.org/10.36306/konjes.1081213
https://search.trdizin.gov.tr/yayin/detay/1144638
https://hdl.handle.net/20.500.13091/3782
ISSN: 2667-8055
Appears in Collections:TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collections

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