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Kirill Tyshchuk, Polina Karpikova, Andrew Spiridonov, Anastasiia Prutianova, Anton Razzhigaev and Alexander Panchenko
Embeddings, i.e., vector representations of objects, such as texts, images, or graphs, play a key role in deep learning methodologies nowadays. Prior research has shown the importance of analyzing the isotropy of textual embeddings for transformer-based ...
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Yao Qin, Yiping Shi, Xinze Hao and Jin Liu
Microblog is an important platform for mining public opinion, and it is of great value to conduct emotional analysis of microblog texts during the current epidemic. Aiming at the problem that most current emotional classification methods cannot effective...
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Benedikt Badanik, Rebeka Remenysegova and Antonin Kazda
This paper focuses on the analysis of traditional methods of service quality evaluation and represents a new sentimental approach to airline service quality evaluation employing user-generated content. It identifies aspects of airline service that passen...
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Ju-Sang Lee, Joon-Choul Shin and Choel-Young Ock
Natural language models brought rapid developments to Natural Language Processing (NLP) performance following the emergence of large-scale deep learning models. Language models have previously used token units to represent natural language while reducing...
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Ho-Min Park and Jae-Hoon Kim
Aspect-based sentiment analysis is a text analysis technique that categorizes data by aspect and identifies the sentiment attributed to each one and a task for a fine-grained sentiment analysis. In order to accurately perform a fine-grained sentiment ana...
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