Sentiment Analysis in Turkish Question Answering Systems: An application of Human-Robot Interaction

نویسندگان

چکیده

The use of the sentiment analysis technique, which aims to extract emotions and thoughts from texts, has become a remarkable research topic today, where importance human-robot interaction is gradually increasing. In this study, new hybrid model proposed using machine learning algorithms increase emotional performance for Turkish question answer systems. context, as first, we apply text preprocessing steps question-answer-emotion dataset. Subsequently, convert preprocessed texts into vector form Pretrained BERT Model two different word representation methods, TF-IDF word2vec. Additionally, incorporate pre-determined polarity vectors containing positive negative scores words question-answer vector. As result propose model. We separate vectorized expanded training testing data train test them with algorithms. By employing previously unused method in question-answering systems, achieve an accuracy value up 91.05% analysis. Consequently, study contributes making interactions more realistic sensitive.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2023

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2023.3291592