… influence of the word normalization on classification task in … word normalization methods.
However, our experiments indicate that word normalization does not affect the text classification …

… Abstract—In this study, we used SVM for text classification. There is stemming or lemmatization
word normalization with the addition of Chi-square feature selection on the classification …

… of text that we would like to normalize (in other words, the tokens are in “Before” column of
Table 2); normalized token refers to the words that … Text classification improved by integrating …

… of four rather distinct text types—news text, a recipes newsgroup, … We report results in terms
of word-error rate, which is … in evaluating text normalization systems. c 2001 Academic Press …

… Nevertheless, the result analysis of words that has been failed to be normalized shows that
our algorithm cannot handle common pattern such as ‘wkwkwkw’, ‘hahaha’, ‘haha’, etc. Thus, …

… most popular algorithms in text classification. In this approach, normalization is an important
… and the number of words in CL F,(1) are almost in proportion with each other. In conclusion, …

… a new text classification model by adding layer normalization, … transformer-based text
classification models including BERT, … All texts were split into a set of words, also known as …

… Naive Bayes for Text Classification with Unbalanced Classes … Fortunately it turns out that
there is a simple remedy: we can normalize the word counts in each class so that the total size …

… text normalization is performed with preprocessing stages such as tokenization, out of word
… Hence, the raw input Twitter text (reviews) will be normalized and finally the polarity gets …

… Since input word embeddings cannot be normalized as explained in Sect. 4.1, we use ELU
activation [26] in the proposed SCNN model instead. ELU activation function is defined as: …