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  2. Content similarity detection - Wikipedia

    en.wikipedia.org/wiki/Content_similarity_detection

    Systems for text similarity detection implement one of two generic detection approaches, one being external, the other being intrinsic. [5] External detection systems compare a suspicious document with a reference collection, which is a set of documents assumed to be genuine. [6]

  3. List of proofreader's marks - Wikipedia

    en.wikipedia.org/wiki/List_of_proofreader's_marks

    These are usually handwritten on the paper containing the text. Symbols are interleaved in the text, while abbreviations may be placed in a margin with an arrow pointing to the problematic text. Different languages use different proofreading marks and sometimes publishers have their own in-house proofreading marks.

  4. Unicheck - Wikipedia

    en.wikipedia.org/wiki/Unicheck

    Unicheck uses an algorithm that searches for similar text on web pages, in open source repositories, and in the user's internal library. Accuracy of search is achieved by using the algorithm that divides text into small shifting sequences and uses them to look for similarities and by using live web index, which enables checks against all web pages.

  5. Fuzzy hashing - Wikipedia

    en.wikipedia.org/wiki/Fuzzy_hashing

    Fuzzy hashing, also known as similarity hashing, [1] is a technique for detecting data that is similar, but not exactly the same, as other data.This is in contrast to cryptographic hash functions, which are designed to have significantly different hashes for even minor differences.

  6. SimHash - Wikipedia

    en.wikipedia.org/wiki/Simhash

    A large scale evaluation has been conducted by Google in 2006 [2] to compare the performance of Minhash and Simhash [3] algorithms. In 2007 Google reported using Simhash for duplicate detection for web crawling [4] and using Minhash and LSH for Google News personalization.

  7. Duplicate characters in Unicode - Wikipedia

    en.wikipedia.org/wiki/Duplicate_characters_in...

    Unicode aims at encoding graphemes, not individual "meanings" ("semantics") of graphemes, and not glyphs.It is a matter of case-by-case judgement whether such characters should receive separate encoding when used in technical contexts, e.g. Greek letters used as mathematical symbols: thus, the choice to have a "micro-sign" µ separate from Greek μ, but not a "Mega sign" separate from Latin M ...

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  9. Wikipedia : Citation templates and reference anchors

    en.wikipedia.org/wiki/Wikipedia:Citation...

    The W3C Validation Service can be used to check for duplicate HTML ids. Where the same author has multiple publications within the same year, the citation template will create a duplicate anchor. The standard solution is to add a lower case alpha character to the year.

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