Relevance of Similarity Measures Usage for Paraphrase Detection

Tedo Vrbanec, Ana Mestrovic

Abstract: The article describes the experiments and their results using two Deep Learning (DL) models and four measures of similarity/distance, determining the similarity of documents from the three publicly available corpora of paraphrased documents. As DL models, Word2Vec was used in two variants and FastText in one. The article explains the existence of a multitude of hyperparameters and defines their values, selection of effective ways of text processing, the use of some non-standard parameters in Natural Language Processing (NLP), the characteristics of the corpora used, the results of the pairs (DL model, similarity measure) processing corpora, and tries to determine combinations of conditions under which use of exactly certain pairs yields the best results (presented in the article), measured by standard evaluation measures Accuracy, Precision, Recall and primarily F-measure.