Titlebook: Analysis of Images, Social Networks and Texts; 7th International Co Wil M. P. van der Aalst,Vladimir Batagelj,Andrey V Conference proceedin

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Literature Review and Research Gap,ssions, the words combine to generate a different meaning. This is why, identification of non-compositional expressions (e.g. idioms) become important in natural language processing tasks such as machine translation and word sense disambiguation..In this study, we explored the performance of vector

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https://doi.org/10.1007/978-3-658-16277-1om different dictionaries are clustered, then single words and multiwords are extracted as hypernym candidates. A classification-based approach on pre-trained word embeddings is implemented as a complementary technique. In total, we extracted about 40K unique hypernym candidates for 22K word entries

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https://doi.org/10.1007/978-3-658-16277-1nditions of telephone conversations is not ideal and contains a lot of mistakes and inaccuracies arising at the stage of speech recognition. Today, there are almost no papers about the sentiment analysis of conversations using multimodal datasets for the Russian language. In this paper, we suggest t

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Inequality and the Digital Economynal neural network for question classification. We took advantage of an existing corpus of 2008 questions, manually annotated in accordance with a pragmatic 14-class typology. We modified the data by reducing the typology to 13 classes, expanding the dataset and improving the representativeness of s

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