alenka
v2.0.2
Published
Predicting Russian names from transliterated and short forms with statistical learning and Levenshtein distance
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Alenka 👧
Alenka is a free library for predicting Russian names (and genders) from transliterated and short forms with statistical learning and Levenshtein distance.
Alenka now is not a tool for inflection (see Lvovich) or parsing first/middle/last Russian names from strings. But it will somewhen be.
Advantages
Useful for social data and media analysis.
🌀 Natively in TypeScript
🔢 Statistically trained
❤ Simple and friendly API
⚙ Configurable
Usage
Install Alenka with npm
or yarn
.
npm i alenka
yarn add alenka
Using with default configuration
import { NamePredictor } from "alenka";
const np = new NamePredictor();
np.predictName('Саня') // 'Александр' as more frequent
np.predictName('Саня', 'female') // 'Александра'
np.predictName('Сирожа') // 'Сергей' due to Levenstein matching
np.predictName('$one4ka') // 'София' due to transliteration rules
np.predictName('asdasda') // undefined
np.predictGender('Соня') // 'female'
np.predictAll('Саня') // [{name: 'Александр', ...}, ...]
Using with custom configuration
import { NamePredictor } from "alenka";
const options = {
useLevenshtein: false,
// minAcceptibleDistance: 1,
// frequenciesSource: 'vk',
// handlingCase: 'ignore',
// handlingYo: 'ignore',
} as const;
const np = new NamePredictor(options);
np.predictName('Сирожа') // 'unedfined'
Terminology
Names
are full forms of Russian Names (e.g.Александр
orСофия
);Shorts
are shotened forms of names (e.g.Саша
orСонечка
);Transliterations
are latin versions of names or shorts (e.g.Alex
orSofia
);Variants
are names, shorts and transliterations together;Tokens
are any strings including variatns (e.g.Саша
,$0nechk@
,abcdefg
).
Prediction
is mapping a token to a name. It happens via mathcing token against a dataset of names, shorts and transliterations with Levenshtein distance to find the closest one and return the relevant name. If nothing matched, undefined will be returned.
Contribution
Feel free to fork and leave pull requests.
To start development just run following familiar commands.
git clone https://github.com/solovevserg/alenka.git
cd alenka
yarn install
yarn test:watch
Roadmap
Here a list of actual tasks to participate at. Thanks in advance for any help.
- Fix problems with handling 'ё'
- Split in the dataset variants for shorts and tranliterations
- Finish README
- Add issues board (bug tracker)
- Add ESLint
- Add missing short forms to the data source
- Write transliteration logic (instead of cyrillic-to-translit-js)
- Optimize performance
About author
I am sergei Solovev, fullstack TS developer, data analyst and teacher. Look at my works here. For fast response get me on telegram
Licesnse
Copyright (c) 2022, Sergei Solovev [email protected]
Permission to use, copy, modify, and/or distribute this software for any purpose with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.