Feb 28, 2025 · Several string similarity measures using tokens were examined and compared. Three of the methods, overlap coefficient, Jaccard index, and dice coefficient, were based on set similarity measures.

Aug 21, 2023 · Token-based algorithms focus on comparing strings based on their constituent tokens or words, rather than individual characters (but sometimes tokens are only characters).

You may use the algorithm of computing the length of the longest common sub-sequence to solve the problem. If the length of the longest common sub-sequence for both the input strings is less than the length of either of the strings, they are unequal.

Jun 7, 2024 · Token-based algorithms for string similarity metrics involve breaking down strings into smaller units, called tokens, and then comparing these tokens to determine the similarity between the strings.

Mar 22, 2023 · Data scientists have developed a wide range of algorithms to assess similarity of text ranging from statistical techniques to deep-learning solutions. In this blog, we begin this discussion with...

Feb 13, 2017 · In this article, we present the results of a wide-ranging evaluation on the performance of different string similarity metrics over the toponym matching task.

Mar 18, 2024 · In this tutorial, we’ll learn about the ways to quantify the similarity of strings. For the most part, we’ll discuss different string distance types available to use in our applications. We’ll overview different metrics and discuss their properties and …

We summarize re-sults obtained from using various string distance met-rics on the task of matching entity names: these metrics include distance functions proposed by several differ-ent communities, including edit-distance metrics, fast heuristic string comparators, token-based distance met-rics, and hybrid methods.

Given two texts A, B being their respective number of tokens jAj and jBj, the Monge-Elkan algorithm measures the average of the similarity values between pairs of more similar tokens within texts A and B.

algorithms can significantly improve the accuracy and time complexity of the calculation of Field Similarity. Keywords: Field Similarity, Pattern Recognition, String Similarity, data cleaning, Record Similarity. [GUS97] D. Guseld. “Algorithms on Strings, Trees and Sequences”, in Computer Science and Computational Biology. CUP, 1997.