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Sort groups of strings into buckets.
Inspired by OpenRefine's clustering.
The unit of analysis is a bucket. It looks like this:
const bucket = {
"commonWord": 3,
"CommonWord": 20,
"SuperRareWord": 1
}
strcluster can break your bucket into bins by computing a bin key for each
string. Here's a code sample, using the bucket
from above:
import { clusterByKey } from 'clustring'
import fingerprint from 'clustring/key/fingerprint'
const bins = clusterByKey(bucket, fingerprint())
// bins is:
// [
// {
// "name": "CommonWord",
// "key": "commonword",
// "count": 23,
// "bucket": { "commonWord": 3, "CommonWord": 20 }
// },
// {
// "name": "SuperRareWord",
// "key": "superrareword",
// "count": 1,
// "bucket": { "SuperRareWord": 1}
// }
// ]
strcluster can also break your bucket into bins using a distance function to compare two strings.
Distance functions aren't cheap. A block-based approach avoids comparisons by grouping strings into "blocks" that all contain the same N sequence of characters. (Effectively, this skips comparisons by assuming infinite distance if there is no such sequence).
Here's some sample code:
import { clusterByKnn } from 'clustring'
import levenshtein from 'clustring/knn/levenshtein'
const bins = clusterByKnn(bucket, levenshtein(2), { blockSize: 5 })
// bins will be same as in previous example.
npm install
npm test -- --watch # runs tests continuously
npm run-script build -- --watch # builds continuously
Pick a feature; write a test; make it pass; commit.
version
in package.json
git commit -m 'vx.x.x && git tag vx.x.x && git push && git push origin vx.x.x
npm publish
FAQs
Algorithms for clustering strings
The npm package clustring receives a total of 35 weekly downloads. As such, clustring popularity was classified as not popular.
We found that clustring demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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