TY - GEN
T1 - On Evaluating the Impact of Automatic Text Summarization on Large Document Classification
T2 - 22nd IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2025
AU - Kahil, Moustafa Sadek
AU - Derdour, Makhlouf
AU - Bouamrane, Amira
AU - Abdellah, Kouzou
AU - Deriche, Mohamed
AU - Sahraoui, Abdelatif
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Document categorization continues to be a significant area of research, particularly in the context of automating the indexing of diverse web content such as blogs and forums. However, large document classification poses challenges in relation with both performance and processing time. This paper empirically investigates the impact of text summarization on document classification. For that, we compare classification performance before and after applying summarization techniques, focusing on two key aspects: (1) computational time and (2) classification performance, measured through accuracy, loss, and F1-score metrics. Our findings demonstrate the effectiveness of the proposed method, highlighting its potential to enhance the efficiency and accuracy of document categorization processes.
AB - Document categorization continues to be a significant area of research, particularly in the context of automating the indexing of diverse web content such as blogs and forums. However, large document classification poses challenges in relation with both performance and processing time. This paper empirically investigates the impact of text summarization on document classification. For that, we compare classification performance before and after applying summarization techniques, focusing on two key aspects: (1) computational time and (2) classification performance, measured through accuracy, loss, and F1-score metrics. Our findings demonstrate the effectiveness of the proposed method, highlighting its potential to enhance the efficiency and accuracy of document categorization processes.
KW - Automatic text summarization
KW - Document Classification
KW - Extractive summarization
KW - Large Text Data
KW - Natural Language Processing
UR - https://www.scopus.com/pages/publications/105007283986
U2 - 10.1109/SSD64182.2025.10989915
DO - 10.1109/SSD64182.2025.10989915
M3 - Conference contribution
AN - SCOPUS:105007283986
T3 - 22nd IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2025
SP - 37
EP - 42
BT - 22nd IEEE International Multi-Conference on Systems, Signals and Devices, SSD 2025
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 February 2025 through 20 February 2025
ER -