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  2. Diff-Text - Wikipedia

    en.wikipedia.org/wiki/Diff-Text

    Any similarity between the two documents above the specified minimum will be reported (if detecting moves is selected). This is the main difference between Diff-Text and most other text comparison algorithms. Diff-Text will always match up significant similarities even if contained within non-identical or moved lines.

  3. Normalized compression distance - Wikipedia

    en.wikipedia.org/wiki/Normalized_compression...

    Normalized compression distance (NCD) is a way of measuring the similarity between two objects, be it two documents, two letters, two emails, two music scores, two languages, two programs, two pictures, two systems, two genomes, to name a few. Such a measurement should not be application dependent or arbitrary.

  4. Content similarity detection - Wikipedia

    en.wikipedia.org/wiki/Content_similarity_detection

    Based on a chosen document model and predefined similarity criteria, the detection task is to retrieve all documents that contain text that is similar to a degree above a chosen threshold to text in the suspicious document. [7] Intrinsic PDSes solely analyze the text to be evaluated without performing comparisons to external documents.

  5. Approximate string matching - Wikipedia

    en.wikipedia.org/wiki/Approximate_string_matching

    Computing E(m, j) is very similar to computing the edit distance between two strings. In fact, we can use the Levenshtein distance computing algorithm for E ( m , j ), the only difference being that we must initialize the first row with zeros, and save the path of computation, that is, whether we used E ( i − 1, j ), E( i , j − 1) or E ( i ...

  6. Bibliographic coupling - Wikipedia

    en.wikipedia.org/wiki/Bibliographic_coupling

    Bibliographic coupling, like co-citation, is a similarity measure that uses citation analysis to establish a similarity relationship between documents. Bibliographic coupling occurs when two works reference a common third work in their bibliographies. It is an indication that a probability exists that the two works treat a related subject ...

  7. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    The mutual information is an information theoretic measure of how much information is shared between a clustering and a ground-truth classification that can detect a non-linear similarity between two clusterings. Normalized mutual information is a family of corrected-for-chance variants of this that has a reduced bias for varying cluster ...

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    mail.aol.com

    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. Fuzzy hashing - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_hashing

    Fuzzy hashing exists to solve this problem of detecting data that is similar, but not exactly the same, as other data. Fuzzy hashing algorithms specifically use algorithms in which two similar inputs will generate two similar hash values. This property is the exact opposite of the avalanche effect desired in cryptographic hash functions.