I searched on the net the different measures of text similarity. And I found many algorithms concerning this issue and there are classified into many categories such:
- Token-Based Measure: Tf-idf, Euclidean, Manhattan, overlap coefficient, matching coefficient, cosine, etc.
- Character-based: Levenshtein, Hamming, Jaro-Winkler, Jaro, etc.
- Q-gram: Jaccard, dice coefficient, etc.
- Mixed Measures: Monge-Elkan, Soft-tfidf
and other categories. In the article Similarity Measures for Title Matching they use different similarity measures and compare the results. But such a result they mention that Levenshtein could be one of the best algorithm for text similarities. Is it efficient with long sentences?