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By allowing a false positive rate for the duplicates, the communication volume can be reduced further as the PEs don't have to send elements with duplicated hashes at all and instead any element with a duplicated hash can simply be marked as a duplicate. As a result, the false positive rate for duplicate detection is the same as the false ...
Metaphone is a phonetic algorithm, published by Lawrence Philips in 1990, for indexing words by their English pronunciation. [1] It fundamentally improves on the Soundex algorithm by using information about variations and inconsistencies in English spelling and pronunciation to produce a more accurate encoding, which does a better job of matching words and names which sound similar.
The following is a list of the 172 most common word duplicates (number after word is count of occurrences) extracted from a search of all English Wikipedia articles existing on 21 February 2006. Most punctuation was automatically removed and so the count is unlikely to be 100% accurate.
Let us recall that, for a list l, |l| denotes its length, that NIL represents an empty list and CONS(h, t) represents the list whose head is h and whose tail is t. The functions drop(i, l) and take(i, l) return the list l without its first i elements, and the first i elements of l, respectively. Or, if |l| < i, they return the empty list and l ...
Then the duplicates will be listed, and must be manually merged. There will often be false positives; web.archive.org URLs, in particular, are a nuisance as they contain the original URLs, which show as duplicates. The optional part of Step 2 eliminates the archive URLs, but unfortunately the list of duplicates includes the archived pages.
The "Van list" included 250 English words. Martin Porter's word stemming program developed in the 1980s built on the Van list, and the Porter list is now commonly used as a default stoplist in a variety of software applications. In 1990, Christopher Fox proposed the first general stop list based on empirical word frequency information derived ...
In computer vision, the bag-of-words model (BoW model) sometimes called bag-of-visual-words model [1] [2] can be applied to image classification or retrieval, by treating image features as words. In document classification , a bag of words is a sparse vector of occurrence counts of words; that is, a sparse histogram over the vocabulary.
Atoms are usually bare words in Prolog code, written with no special syntax. However, atoms containing spaces or certain other special characters must be surrounded by single quotes. Atoms beginning with a capital letter must also be quoted, to distinguish them from variables. The empty list, written [], is also an atom.