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Author: Admin | 2025-04-28
Vector was calculated using the sum of the vectors divided by the number of words in a phrase: V = a v e r a g e v e c t o r = s u m ( v e c t o r s ) n u m b e r o f w o r d s i n a p h r a s e (1) Given any two average vectors V A and V B of two phrases, the cosine similarity, c o s θ , is represented by S i m i l a r i t y = cos θ = ∑ i = 1 n V A i V B i ∑ i = 1 n V A i 2 ∑ i = 1 n V B i 2 (2) Next, a sparse matrix (e.g., a vocabulary dense matrix) for stressed corpus was calculated by transforming those tokenized and vectorized tweets using frequency inverse document frequency (TFIDF). The mathematical formula of TFIDF is illustrated below: t f i d f ( t , d , D ) = t f ( t , d ) ∗ i d f ( t , D ) , (3) where t denotes the terms; d denotes each document; and D denotes the collection of documents. The first part of the formula t f ( t , d ) calculates the number of times each word in COVID-19 corpus appeared in each document. The second part of
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