Comparative Study of Clustering Techniques for Extractive Text Summarization

Author:

Yadav Sushant,Singhal Archana

Publisher

Springer Nature Singapore

Reference14 articles.

1. Sharaff A, Shrawgi H, Arora P, Verma A (2017) Document summarization by agglomerative nested clustering approach. In: 2016 IEEE International Conference Advances Electronics Communication Computer Technology (ICAECCT) 2016, pp 187–191, IEEE, Pune, India

2. Zhao C, Peng Q, Sun S (2009) Chinese text automatic summarization based on affinity propagation cluster. 2009 sixth international conference on fuzzy systems and knowledge discovery. FSKD 2009, 1. IEEE, Tianjin, China, pp 425–429

3. Khan R, Qian Y, Naeem S (2019) Extractive based text summarization using KMeans and TF-IDF. Inter J Inform Eng Electr Bus (IJIEEB) 11(3):33–44

4. Agrawal A, Gupta U (2014) Extraction based approach for text summarization using k-means clustering. Intern J Sci Res Publ 4(1):2250–3153

5. Weigand AC, Lange D, Rauschenberger M (2021) How can small data sets be clustered?. In: Mensch und Computer 2021, Workshopband, Workshop on User-Centered Artificial Intelligence (UCAI ’21)

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