JOURNAL ARTICLE

Extractive Text Summarization Technique Using Fuzzy C-Means Clustering Algorithm

Shafiul GaniJia UddinIftekharul Mobin

Year: 2019 Journal:   2019 International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2) Pages: 1-6

Abstract

Text summarization process has become one of the significant research areas for years owing to cope up with the astounding increase of virtual textual materials. Text summarization is the process to keep the relevant important information of the original text in a shorter version with the main ideas of the original text. There are two main classifications of text summarization process Extractive and Abstractive text summarization, Extractive summarization processes by using most important fragments of existing words, phrases or sentences from the original document, A sentence based mode) using Fuzzy C-Means clustering has been proposed in this research. Six best key features including a new feature "Sentence Highlighter Feature" have been introduced for the sentence scoring. Performance of the proposed FCM mode) is evaluated by ROUGE, which has been gauged with the precision, recall and f-measure. The result shows that this FCM model extractive techniques with a less outline repetition and profundity of data.

Keywords:
Automatic summarization Computer science Cluster analysis Fuzzy clustering Fuzzy logic Artificial intelligence Data mining Algorithm Pattern recognition (psychology)

Metrics

6
Cited By
0.13
FWCI (Field Weighted Citation Impact)
22
Refs
0.54
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Web Data Mining and Analysis
Physical Sciences →  Computer Science →  Information Systems
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence

Related Documents

© 2026 ScienceGate Book Chapters — All rights reserved.