Open Source JavaScript Natural Language Processing (NLP) Tools
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JavaScript Natural Language Processing (NLP) Tools
View 188 business solutionsBrowse free open source JavaScript Natural Language Processing (NLP) Tools and projects below. Use the toggles on the left to filter open source JavaScript Natural Language Processing (NLP) Tools by OS, license, language, programming language, and project status.
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compromise
Modest natural-language processing
Language is complicated and there's a gazillion words. Compromise is a javascript library that interprets and pre-parses text and makes some reasonable decisions so things are way easier. Compromise tries its best to parse text. it is small, quick, and often good-enough. It is not as smart as you'd think. Conjugate and negate verbs in any tense. Play between plural, singular and possessive forms. Interpret plain-text numbers. Handle implicit terms. Use it on the client-side or as an es-module. compromise is 180kb (minified). It's pretty fast. It can run on keypress. It works mainly by conjugating all forms of a basic word list. Decide how words get interpreted or make heavier changes with a compromise-plugin. Parse text without running POS-tagging. Pre-parse any match statements for faster lookups. It is not the most accurate, or clever nlp library, but found its niche as an easy, small library that can run everywhere. -
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Search-Index
A persistent, network resilient, full text search library
Search-Index is a lightweight and fast JavaScript-based search engine that enables full-text search indexing and retrieval for web applications. -
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kener
Kener is a Modern Self hosted Status Page, batteries included
Kener: Open-source Node.js status page tool, designed to make service monitoring and incident handling a breeze. It offers a sleek and user-friendly interface that simplifies tracking service outages and improves how we communicate during incidents. And the best part? Kener integrates seamlessly with GitHub, making incident management a team effort—making it easier for us to track and fix issues together in a collaborative and friendly environment. -
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Rasa-UI
Rasa UI is a frontend for the Rasa Framework
Rasa UI is a web application built on top of, and for Rasa. Rasa UI provides a web application to quickly and easily be able to create and manage bots, NLU components (Regex, Examples, Entities, Intents, etc.) and Core components (Stories, Actions, Responses, etc.) through a web interface. It also provides some convenience features for Rasa, like training and loading your models, monitoring usage or viewing logs. -
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AIVA (A.I. Virtual Assistant)
AIVA (A.I. Virtual Assistant): General-purpose virtual assistant
AIVA is a general-purpose virtual assistant designed for developers, enabling the creation of customizable AI assistants for various applications. -
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franc
Natural language detection
Franc is a lightweight language detection library for JavaScript that supports multiple languages and scripts. It is designed for detecting text language efficiently in various applications. -
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NLP.js
An NLP library for building bots
NLP.js is an NLP library for building bots, with entity extraction, sentiment analysis, automatic language identifier, and much more. "NLP.js" is a general natural language utility for nodejs. Search the best substring of a string with less Levenshtein distance to a given pattern. Get stemmers and tokenizers for several languages. Sentiment Analysis for phrases (with negation support). Named Entity Recognition and management, multi-language support, and acceptance of similar strings, so the introduced text does not need to be exact. Natural Language Processing Classifier, to classify an utterance into intents. NLP Manager, a tool able to manage several languages, the Named Entities for each language, the utterances, and intents for the training of the classifier, and for a given utterance return the entity extraction, the intent classification and the sentiment analysis. -
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Parsr
Transforms PDF, Documents and Images into Enriched Structured Data
Parsr is an open-source document parsing tool that converts PDFs, scanned images, and other structured documents into structured, machine-readable data formats. -
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natural
General natural language facilities for node
"Natural" is a general natural language facility for nodejs. It offers a broad range of functionalities for natural language processing. Tokenizing, stemming, classification, phonetics, tf-idf, WordNet, string similarity, and some inflections are currently supported. It’s still in the early stages, so we’re very interested in bug reports, contributions and the like. Note that many algorithms from Rob Ellis’s node-nltools are being merged into this project and will be maintained from here onward. While most of the algorithms are English-specific, contributors have implemented support for other languages. Russian stemming has been added and Spanish stemming has been added, as well. Stemming and tokenizing in more languages have been added. If you’re just looking to use natural without your own node application, you can install via NPM. -
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Wink-NLP
Developer friendly Natural Language Processing
Wink-NLP is a lightweight and fast natural language processing library for JavaScript, optimized for browser and Node.js environments. -
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sentiment
AFINN-based sentiment analysis for Node.js
Sentiment is a simple and lightweight sentiment analysis tool for Node.js that evaluates the polarity of text by scoring words based on positive and negative sentiment. -
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Arabic Corpus
Text categorization, arabic language processing, language modeling
The Arabic Corpus {compiled by Dr. Mourad Abbas ( http://sites.google.com/site/mouradabbas9/corpora ) The corpus Khaleej-2004 contains 5690 documents. It is divided to 4 topics (categories). The corpus Watan-2004 contains 20291 documents organized in 6 topics (categories). Researchers who use these two corpora would mention the two main references: (1) For Watan-2004 corpus ---------------------- M. Abbas, K. Smaili, D. Berkani, (2011) Evaluation of Topic Identification Methods on Arabic Corpora,JOURNAL OF DIGITAL INFORMATION MANAGEMENT,vol. 9, N. 5, pp.185-192. 2) For Khaleej-2004 corpus --------------------------------- M. Abbas, K. Smaili (2005) Comparison of Topic Identification Methods for Arabic Language, RANLP05 : Recent Advances in Natural Language Processing ,pp. 14-17, 21-23 september 2005, Borovets, Bulgary. More useful references to check: ------------------------------------------- https://sites.google.com/site/mouradabbas9/corpora -
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MITRE Annotation Toolkit
A toolkit for managing and manipulating text annotations
The MITRE Annotation Toolkit (MAT) is a suite of tools which can be used for automated and human tagging of annotations. Annotation is a process, used mostly by researchers in natural language processing, of enhancing documents with information about the various phrase types the documents contain. MAT supports both UI interaction and command-line interaction, and provides various levels of control over the overall annotation process. It can be customized for specific tasks (e.g., named entity identification, de-identification of medical records). The goal of MAT is not to help you configure your training engine (in the default case, the Carafe CRF system) to achieve the best possible performance on your data. MAT is for "everything else": all the tools you end up wishing you had. -
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AILOKS
A polylingual dictionary/ontology system
AILOKS is an acronym for Artificial Intelligence Linguistic Object Knowledge System. This dictionary is aimed to facilitate advanced NLP, translation engines and provide an effective dictionary interface to humans. This dictionary is Polylingual and should prove useful to language students, linguists and translators alike. It is part of a series of interrelated projects. -
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This project aims to process free text from ProMED emails and other electronic resources to visualize outbreak/epidemic summaries using combined natural language processing and visualization algorithms.
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Graphical Grammar Studio
An user friendly grammar tool for natural language processing tasks
Full documentation with tutorials is included in the download package. Graphical Grammar Studio is a tool for applying grammars which behave as words acceptors/consumers and annotators. GGS grammars can be used to find and annotate sequences of words which respect certain conditions, in a given input. Its purpose is for creating NLP tools like phrase chunkers, named entity finders, pronoun co-reference solvers etc. A grammar is represented by a state machine which can be visualized, edited and applied. A grammar is organized in graphs of nodes. Nodes are used for consuming words from the input, for executing jumps to other graphs in the grammar or for creating annotations etc. GGS has a unique feature: It allows the user to write JavaScript code to be executed for nodes of the grammar. This is useful for checking grammatical agreements but not only. The user can: declare variables (including complex js structures), check for boolean conditions, use variables in annotations etc. -
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Service Grid - Language Grid Base System
SOA infrastracture initially developed by NICT Language Grid Project
Service Grid is an infrastructure for accumulating and sharing Web services. Resources with complicated intellectual property issues are wrapped as Web services and shared on the Service Grid. If you release your software by using the software of this project, please include the following description in the documents or on the website. * This software uses the [SOFTWARE] by the Language Grid project (http://langrid.org/). [SOFTWARE] is one of: * Service Grid Server Software (http://langrid.org/oss-project/en/service_grid.html) * Language Service Development Libraries (http://langrid.org/oss-project/en/language_service.html) * Language Grid Toolbox (http://langrid.org/oss-project/en/toolbox.html) If you publish a paper by using the software of this project, please cite the following book. * Toru Ishida Ed. The Language Grid: Service-Oriented Collective Intelligence for Laguage Resource Interoperability. Springer, 2011. ISBN 978-3-642-21177-5.
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