Describing Wordsfor Attrition

examples: nosewinterblue eyeswoman

Here are some adjectives for attrition: particularly smooth and bright, unthinkably high, vexatiously incessant, distasteful social, sure normal, possibly finer, particularly smooth, trial and rough, mutual social, steady relentless, still rapid, systematic literary, still virtual, otherwise constant, continual and rapid, slow but continuous, spiritual or material, much mechanical, much rough, long and constant, significantly higher, such constant, more rapid, long-haul, extremely high, such powerful, gradual, unacceptable, continual, still less. You can get the definitions of these attrition adjectives by clicking on them. You might also like some words related to attrition (and find more here).

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Words to Describe attrition

Below is a list of describing words for attrition. You can sort the descriptive words by uniqueness or commonness using the button above. Sorry if there's a few unusual suggestions! The algorithm isn't perfect, but it does a pretty good job for most common nouns. Here's the list of words that can be used to describe attrition:

particularly smooth and bright unthinkably high vexatiously incessant distasteful social sure normal possibly finer particularly smooth trial and rough mutual social steady relentless still rapid systematic literary still virtual otherwise constant continual and rapid slow but continuous spiritual or material much mechanical much rough long and constant significantly higher such constant more rapid long-haul extremely high such powerful gradual unacceptable
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continual still less contrite rapid constant mutual much lower steady crucial incessant little further mechanical unceasing maximum fortuitous insatiable hardest unavoidable pitiless defensive ongoing injurious considerable thunderous inevitable sheer glacial metropolitan slow perennial manual normal fearful natural perpetual laborious irritating amorous much less prodigious frequent physical continuous manifest bloody relentless severe high excessive brisk mere supernatural stern trial indirect consequent extreme finer social ceaseless further alarming nervous slight everyday current silent slightest temporal grim ruthless vulgar material external musical long net rough quick psychic latest bright subsequent virtual astonishing intellectual pure fair internal spiritual gentle dry dreadful active emotional worse incredible official simple mental moral serious genuine national equal recent powerful heavy sharp literary actual violent curious perfect necessary mighty less higher faint awful lower mysterious complete massive terrible local certain general

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Words to Describe attrition

As you've probably noticed, adjectives for "attrition" are listed above. According to the algorithm that drives this website, the top 5 adjectives for "attrition" are: particularly smooth and bright, unthinkably high, vexatiously incessant, distasteful social, and sure normal. There are 151 other words to describe attrition listed above. Hopefully the above generated list of words to describe attrition suits your needs.

If you're getting strange results, it may be that your query isn't quite in the right format. The search box should be a simple word or phrase, like "tiger" or "blue eyes". A search for words to describe "people who have blue eyes" will likely return zero results. So if you're not getting ideal results, check that your search term, "attrition" isn't confusing the engine in this manner.

Note also that if there aren't many attrition adjectives, or if there are none at all, it could be that your search term has an abiguous part-of-speech. For example, the word "blue" can be an noun and an adjective. This confuses the engine and so you might not get many adjectives describing it. I may look into fixing this in the future. You might also be wondering: What type of word is attrition?

Describing Words

The idea for the Describing Words engine came when I was building the engine for Related Words (it's like a thesaurus, but gives you a much broader set of related words, rather than just synonyms). While playing around with word vectors and the "HasProperty" API of conceptnet, I had a bit of fun trying to get the adjectives which commonly describe a word. Eventually I realised that there's a much better way of doing this: parse books!

Project Gutenberg was the initial corpus, but the parser got greedier and greedier and I ended up feeding it somewhere around 100 gigabytes of text files - mostly fiction, including many contemporary works. The parser simply looks through each book and pulls out the various descriptions of nouns.

Hopefully it's more than just a novelty and some people will actually find it useful for their writing and brainstorming, but one neat little thing to try is to compare two nouns which are similar, but different in some significant way - for example, gender is interesting: "woman" versus "man" and "boy" versus "girl". On an inital quick analysis it seems that authors of fiction are at least 4x more likely to describe women (as opposed to men) with beauty-related terms (regarding their weight, features and general attractiveness). In fact, "beautiful" is possibly the most widely used adjective for women in all of the world's literature, which is quite in line with the general unidimensional representation of women in many other media forms. If anyone wants to do further research into this, let me know and I can give you a lot more data (for example, there are about 25000 different entries for "woman" - too many to show here).

The blueness of the results represents their relative frequency. You can hover over an item for a second and the frequency score should pop up. The "uniqueness" sorting is default, and thanks to my Complicated Algorithm™, it orders them by the adjectives' uniqueness to that particular noun relative to other nouns (it's actually pretty simple). As you'd expect, you can click the "Sort By Usage Frequency" button to adjectives by their usage frequency for that noun.

Special thanks to the contributors of the open-source mongodb which was used in this project.

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