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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]
The dictionary contains 157,000 combinations and derivatives, and 169,000 phrases and combinations, making a total of over 600,000 word-forms. [40] [41] There is one count that puts the English vocabulary at about 1 million words—but that count presumably includes words such as Latin species names, prefixed and suffixed words, scientific ...
It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a classifier. [1] It has also been used for computer vision. [2]
A sample test using an automated Gunning Fog calculator on a random footnote from the text (#51: Dion, vol. I. lxxix. p. 1363. Herodian, l. v. p. 189.) [9] gave an index of 19.2 using only the sentence count, and an index of 12.5 when including independent clauses. This brought down the fog index from post-graduate to high school level.
The 609 million words in fact span the 1.3 million bona fide articles, the remaining 100,000 linked articles, and the unknown number of articles without links. A rough estimate of the word count in the latter two categories is ten million words. Dividing the remaining 600 million words by 1.3 million gives a mean article length of about 460 words.
For example, under such a method applied to plain English text the phrase "I run" counts as one word, but "rhinoceros" and "let's talk" would both count as two. Karat et al. found in one study of average computer users in 1999 that the average rate for transcription was 32.5 words per minute, and 19.0 words per minute for composition. [2]
The Coleman–Liau index is a readability test designed by Meri Coleman and T. L. Liau to gauge the understandability of a text. Like the Flesch–Kincaid Grade Level, Gunning fog index, SMOG index, and Automated Readability Index, its output approximates the U.S. grade level thought necessary to comprehend the text.
The formula was inspired by Rudolf Flesch's Flesch–Kincaid readability test which used word-length to determine how difficult a word was for readers to understand. [1] Edgar Dale and Jeanne Chall instead used a list of 769 words that 80% of fourth-grade students were familiar with, such as "no", "yes", and other such very basic words to ...
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