Extractive Text Summarization of Student Essay Assignment Using Sentence Weight Features and Fuzzy C-Means

International Journal of artificial intelligence research

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Field Value
 
Title Extractive Text Summarization of Student Essay Assignment Using Sentence Weight Features and Fuzzy C-Means
 
Creator Suwija Putra, I Made
Adiwinata, Yonatan
Singgih Putri, Desy Purnami
Sutramiani, Ni Putu
 
Subject Computer Science; Text Mining; Information Retrieval;
Text Summarization; Essay Assignments; Weight Sentences; Fuzzy C-Means
 
Description One of the main tasks of a lecturer is to give students an academic assessment in the learning process. The assessment process begins with reading or checking the answers of student assignments that contain a combination of very long sentences such as essay or report assignments. This certainly takes a lot of time to get the primary information contained therein. It is necessary to summarize the answers so that the lecturer does not need to read the whole document but is still able to take the essence of the response to the task. This study proposes the application of summarizing text documents of student essay assignments automatically using the Fuzzy C-Means method with the sentence weighting feature. The sentence weighting feature is used by selecting the sentence with the highest weight in one cluster, helping the system to get the primary information from a document quickly. The results of this study indicate that the system succeeds in summarizing text with an average evaluation of the values of precision, recall, accuracy, and F-measure of 0.52, 0.54, 0.70, and 0.52, respectively.One of the main tasks of a lecturer is to give students an academic assessment in the learning process. The assessment process begins with reading or checking the answers of student assignments that contain a combination of very long sentences such as essay or report assignments. This certainly takes a lot of time to get the primary information contained therein. It is necessary to summarize the answers so that the lecturer does not need to read the whole document but is still able to take the essence of the response to the task. This study proposes the application of summarizing text documents of student essay assignments automatically using the Fuzzy C-Means method with the sentence weighting feature. The sentence weighting feature is used by selecting the sentence with the highest weight in one cluster, helping the system to get the primary information from a document quickly. The results of this study indicate that the system succeeds in summarizing text with an average evaluation of the values of precision, recall, accuracy, and F-measure of 0.52, 0.54, 0.70, and 0.52, respectively.
 
Publisher STMIK Dharma Wacana
 
Contributor
 
Date 2021-01-05
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Identifier http://ijair.id/index.php/ijair/article/view/187
10.29099/ijair.v5i1.187
 
Source International Journal of Artificial Intelligence Research; Vol 5, No 1 (2021): Articles in press
2579-7298
10.29099/ijair.v5i1
 
Language en
 
Rights Copyright (c) 2021 International Journal of Artificial Intelligence Research
https://creativecommons.org/licenses/by-sa/4.0
 

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