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Word Embeddings and Validity Indexes in Fuzzy Clustering
[article]
2022
arXiv
pre-print
In the new era of internet systems and applications, a concept of detecting distinguished topics from huge amounts of text has gained a lot of attention. These methods use representation of text in a numerical format -- called embeddings -- to imitate human-based semantic similarity between words. In this study, we perform a fuzzy-based analysis of various vector representations of words, i.e., word embeddings. Also we introduce new methods of fuzzy clustering based on hybrid implementation of
arXiv:2205.06802v1
fatcat:7e755ztnnrgetierk4mzvta3ee