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Frequency analysis, the study of the frequency of letters or groups of letters; Letter frequencies; Oxford English Corpus; Swadesh list, a compilation of basic concepts for the purpose of historical-comparative linguistics; Zipf's law, a theory stating that the frequency of any word is inversely proportional to its rank in a frequency table
Word frequency is known to have various effects (Brysbaert et al. 2011; Rudell 1993). Memorization is positively affected by higher word frequency, likely because the learner is subject to more exposures (Laufer 1997). Lexical access is positively influenced by high word frequency, a phenomenon called word frequency effect (Segui et al.).
Word count is commonly used by translators to determine the price of a translation job. Word counts may also be used to calculate measures of readability and to measure typing and reading speeds (usually in words per minute). When converting character counts to words, a measure of 5 or 6 characters to a word is generally used for English. [1]
A plot of the frequency of each word as a function of its frequency rank for two English language texts: Culpeper's Complete Herbal (1652) and H. G. Wells's The War of the Worlds (1898) in a log-log scale. The dotted line is the ideal law y ∝ 1 / x
The California Job Case was a compartmentalized box for printing in the 19th century, sizes corresponding to the commonality of letters. The frequency of letters in text has been studied for use in cryptanalysis, and frequency analysis in particular, dating back to the Arab mathematician al-Kindi (c. AD 801–873 ), who formally developed the method (the ciphers breakable by this technique go ...
This corpus first set the bar for the scientific study of the frequency and distribution of word categories in everyday language use. Compiled by Henry Kučera and W. Nelson Francis at Brown University , in Rhode Island , it is a general language corpus containing 500 samples of English, totaling roughly one million words, compiled from works ...
Interactive word clouds and word frequency tables can now be obtained directly on keyword retrieval and keyword-in-context (KWIC) results allowing one to quickly identify words associated with specific content categories, or those appearing, before, after a specific target item.
Even misspelled words, non-words, and words with numbers in them are indexed and stemmed in this way. By adding different forms of the same word to the indexed search query, stemming is a standard method search engines use to aggressively garner more search results to then run a bunch of page-ranking rules against.