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1 A text summarization method based on fuzzy rules and applicable to automated assessment
یک روش خلاصه سازی متن بر اساس قوانین فازی و قابل استفاده برای ارزیابی خودکار-2019
In the last two decades, the text summarization task has gained much importance because of the large amount of online data, and its potential to extract useful information and knowledge in a way that could be easily handled by humans and used for a myriad of purposes, including expert systems for text assess- ment. This paper presents an automatic process for text assessment that relies on fuzzy rules on a vari- ety of extracted features to find the most important information in the assessed texts. The automatically produced summaries of these texts are compared with reference summaries created by domain experts. Differently from other proposals in the literature, our method summarizes text by investigating correlated features to reduce dimensionality, and consequently the number of fuzzy rules used for text summariza- tion. Thus, the proposed approach for text summarization with a relatively small number of fuzzy rules can benefit development and use of future expert systems able to automatically assess writing. The pro- posed summarization method has been trained and tested in experiments using a dataset of Brazilian Portuguese texts provided by students in response to tasks assigned to them in a Virtual Learning En- vironment (VLE). The proposed approach was compared with other methods including a naive baseline, Score, Model and Sentence, using ROUGE measures. The results show that the proposal provides better f-measure (with 95% CI) than aforementioned methods.
Keywords: Text assessment | Computer-assisted assessment | Automatic text summarization | Fuzzy logic
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