Letter2vec+Freq2vec: A Comprehensive Approach to Text Vectorization and Predicting Word Difficulty
Songru Li,
Yuan Cheng,
Hanbin Lu
Abstract:This paper introduces the self-developed word embedded algorithm Letter2vec+Freq2vec. It combines with biKmeans and Stacking algorithm to judge word difficulty in Wordle. The algorithm combines Letter2vec, which models letter interactions and context, and Freq2vec, which calculates letter frequencies at different positions of words to produce a more comprehensive text vectorization method. The results show that this algorithm can get better results than BERT algorithm in small sample size when vectorizing a si… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.