natural vs compromise vs franc vs linguist-js
Natural Language Processing Libraries Comparison
1 Year
naturalcompromisefranclinguist-jsSimilar Packages:
What's Natural Language Processing Libraries?

Natural Language Processing (NLP) libraries are essential tools for developers working with text data, enabling them to analyze, understand, and generate human language in a meaningful way. These libraries provide various functionalities such as language detection, tokenization, part-of-speech tagging, and more, making it easier to build applications that can interact with users in natural language. The choice of an NLP library can significantly impact the efficiency and effectiveness of text processing tasks, depending on the specific requirements of the project.

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natural215,78110,71113.8 MB817 months agoMIT
compromise90,57011,6182.58 MB113a month agoMIT
franc34,4344,205272 kB5a year agoMIT
linguist-js29,61441298 kB118 days agoISC
Feature Comparison: natural vs compromise vs franc vs linguist-js

Language Detection

  • natural:

    Natural does not focus specifically on language detection but can be integrated with other libraries for this purpose, providing a more comprehensive NLP solution.

  • compromise:

    Compromise does not specialize in language detection but can handle basic text processing tasks in various languages once the language is known.

  • franc:

    Franc excels in language detection, capable of identifying over 400 languages with high accuracy. It uses n-grams to analyze text and determine the most likely language, making it a go-to choice for multilingual applications.

  • linguist-js:

    Linguist-js is designed to detect programming languages rather than natural languages, making it ideal for analyzing code repositories and identifying the languages used in source files.

Text Processing Capabilities

  • natural:

    Natural provides extensive text processing capabilities, including tokenization, stemming, classification, and sentiment analysis, making it suitable for a wide range of NLP tasks.

  • compromise:

    Compromise offers a range of text processing capabilities, including part-of-speech tagging, noun phrase extraction, and text transformation. It is designed for quick and efficient manipulation of natural language text.

  • franc:

    Franc is limited to language detection and does not provide text processing capabilities beyond identifying the language of a given text.

  • linguist-js:

    Linguist-js focuses on analyzing programming languages and does not provide general text processing functionalities for natural language.

Performance

  • natural:

    Natural is comprehensive but may have performance trade-offs due to its extensive feature set. It is suitable for applications where a wide range of NLP functionalities is required, but performance optimization may be necessary for large datasets.

  • compromise:

    Compromise is lightweight and optimized for performance, allowing for fast text processing without significant overhead. It is suitable for applications where speed is a priority.

  • franc:

    Franc is designed for high performance in language detection, providing quick results even with large text inputs, making it efficient for real-time applications.

  • linguist-js:

    Linguist-js is efficient in analyzing code and can quickly identify programming languages, but its performance may vary depending on the complexity of the code being analyzed.

Ease of Use

  • natural:

    Natural has a steeper learning curve due to its comprehensive feature set, but it provides extensive documentation and examples to help developers get started.

  • compromise:

    Compromise is user-friendly and has a straightforward API, making it easy for developers to integrate into their applications without a steep learning curve.

  • franc:

    Franc is simple to use, with minimal setup required for language detection, making it accessible for developers who need quick language identification.

  • linguist-js:

    Linguist-js is designed for developers familiar with language analysis; however, it may require some understanding of programming language syntax for effective use.

Extensibility

  • natural:

    Natural is extensible and allows developers to add custom algorithms and models, making it suitable for specialized NLP tasks.

  • compromise:

    Compromise is designed to be extensible, allowing developers to create custom plugins and enhance its capabilities for specific use cases.

  • franc:

    Franc is not designed for extensibility; it focuses solely on language detection without providing hooks for additional functionality.

  • linguist-js:

    Linguist-js can be extended to support additional programming languages, making it flexible for developers working with diverse codebases.

How to Choose: natural vs compromise vs franc vs linguist-js
  • natural:

    Choose Natural if you are looking for a comprehensive NLP toolkit that includes a wide range of functionalities such as tokenization, stemming, classification, and phonetics. It is suitable for more complex NLP tasks and provides a robust set of tools for building sophisticated language processing applications.

  • compromise:

    Choose Compromise if you need a lightweight library focused on natural language understanding and manipulation, particularly for tasks like parsing, tagging, and transforming text. It is ideal for applications that require quick and simple text processing without the overhead of more complex NLP solutions.

  • franc:

    Choose Franc if your primary requirement is language detection. It is a fast and efficient library that can identify over 400 languages, making it suitable for applications that need to handle multilingual content or require language identification as a preprocessing step.

  • linguist-js:

    Choose Linguist-js if you need a library that can analyze and classify programming languages in addition to natural languages. It is particularly useful for applications that involve code analysis or require language detection in source code files, providing insights into the languages used in a codebase.

README for natural

natural

NPM version Node.js CI JavaScript Style Guide GitHub Super-Linter Coverage Status CII Best Practices TypeScript support

"Natural" is a general natural language facility for nodejs. It offers a broad range of functionalities for natural language processing. Documentation can be found here on GitHub Pages.

Open source licenses

Natural: MIT License

Copyright (c) 2011, 2012 Chris Umbel, Rob Ellis, Russell Mull, Hugo W.L. ter Doest

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

WordNet License

This license is available as the file LICENSE in any downloaded version of WordNet. WordNet 3.0 license: (Download)

WordNet Release 3.0 This software and database is being provided to you, the LICENSEE, by Princeton University under the following license. By obtaining, using and/or copying this software and database, you agree that you have read, understood, and will comply with these terms and conditions.: Permission to use, copy, modify and distribute this software and database and its documentation for any purpose and without fee or royalty is hereby granted, provided that you agree to comply with the following copyright notice and statements, including the disclaimer, and that the same appear on ALL copies of the software, database and documentation, including modifications that you make for internal use or for distribution. WordNet 3.0 Copyright 2006 by Princeton University. All rights reserved. THIS SOFTWARE AND DATABASE IS PROVIDED "AS IS" AND PRINCETON UNIVERSITY MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, PRINCETON UNIVERSITY MAKES NO REPRESENTATIONS OR WARRANTIES OF MERCHANT- ABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF THE LICENSED SOFTWARE, DATABASE OR DOCUMENTATION WILL NOT INFRINGE ANY THIRD PARTY PATENTS, COPYRIGHTS, TRADEMARKS OR OTHER RIGHTS. The name of Princeton University or Princeton may not be used in advertising or publicity pertaining to distribution of the software and/or database. Title to copyright in this software, database and any associated documentation shall at all times remain with Princeton University and LICENSEE agrees to preserve same.

Porter stemmer German: BSD License

The Porter stemmer for German is licensed by a BSD license. It states Standard BSD License in the source code, interpreted as the original BSD license consisting of four clauses.