Software Alternatives, Accelerators & Startups

Google Cloud Natural Language API VS NLP.js

Compare Google Cloud Natural Language API VS NLP.js and see what are their differences

Google Cloud Natural Language API logo Google Cloud Natural Language API

Natural language API using Google machine learning

NLP.js logo NLP.js

An NLP library for building bots, with entity extraction, sentiment analysis, automatic language identify, and so more - axa-group/nlp.js
  • Google Cloud Natural Language API Landing page
    Landing page //
    2023-08-06
  • NLP.js Landing page
    Landing page //
    2023-08-02

Google Cloud Natural Language API features and specs

  • Comprehensive Language Support
    Google Cloud Natural Language API supports multiple languages, allowing for a wider range of applications across different locales.
  • Pre-trained Models
    The API uses Google's sophisticated, pre-trained machine learning models, which means it can deliver high-quality results without requiring extensive tuning.
  • Integration with Other Google Services
    The API integrates seamlessly with other Google Cloud services, such as Google Cloud Storage and BigQuery, which can enhance data processing workflows.
  • Real-time Processing
    The API is capable of real-time language processing, making it suitable for applications that require immediate insights.
  • Entity Recognition and Sentiment Analysis
    Offers robust features like entity recognition, sentiment analysis, and syntactic analysis, providing deep insights into text data.
  • Scalability
    Being a cloud-based service, it can scale effortlessly to handle large volumes of text data, suitable for both small and enterprise-level applications.

Possible disadvantages of Google Cloud Natural Language API

  • Cost
    Usage of the API incurs costs based on the number of requests, which could become expensive for large-scale applications or continuous use.
  • Data Privacy Concerns
    As with any cloud service, sending sensitive data to an external server can raise privacy and compliance issues.
  • Limited Customization
    While the pre-trained models are powerful, the API offers limited options for customizing these models to meet specific needs or use cases.
  • Dependency on Internet Connection
    The API requires a reliable internet connection to function, which could be a limitation in areas with unstable connectivity.
  • Latency
    While generally offering real-time processing, network latency can introduce delays, especially with large data volumes or in less optimal network conditions.
  • Learning Curve
    Implementing and integrating the API requires some level of technical knowledge and understanding of natural language processing, which may pose an initial learning curve.

NLP.js features and specs

No features have been listed yet.

Category Popularity

0-100% (relative to Google Cloud Natural Language API and NLP.js)
NLP And Text Analytics
90 90%
10% 10
Spreadsheets
85 85%
15% 15
Natural Language Processing
AI
100 100%
0% 0

User comments

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Social recommendations and mentions

Based on our record, Google Cloud Natural Language API should be more popular than NLP.js. It has been mentiond 14 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Google Cloud Natural Language API mentions (14)

  • Text-based language processing enhanced with AI/ML
    On this family summer trip to Asia, I've admittedly been relying heavily on Google Translate. As someone who lives in the world of APIs, that makes me think of "its API,"^ the Google Cloud Translation API. Pure translation, though, is not the same as finding the right words (although they're similar), and that makes me think of natural language understanding (NLU). When considering NLU and NLP (natural language... - Source: dev.to / 10 months ago
  • Best AI SEO Tools for NLP Content Optimization
    Google Cloud Natural Language API: Google's NLP API offers one of the best AI platforms for sentiment analysis, entity recognition, and syntax analysis to understand and extract information from text. Source: over 1 year ago
  • What do you think AI will replace SEO ?
    Voice search is another area where AI is reshaping SEO services. As more people use voice-activated devices, the way they search for information online is changing. AI algorithms are adept at processing natural language, allowing businesses in Chandigarh to tailor their content to match conversational queries. Optimizing for voice search is becoming a crucial aspect of SEO, and AI is at the forefront of driving... Source: over 1 year ago
  • Natural Language API demo
    Can anyone get the "ANALYZE" button on https://cloud.google.com/natural-language to do anything? Source: almost 2 years ago
  • From pixels to information with Document AI
    We’re seeing successively difficult problems getting solved thanks to machine learning (ML) models. For example, Natural Language AI and Vision AI extract insights from text and images, with human-like results. They solve problems central to the way we communicate:. - Source: dev.to / about 2 years ago
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NLP.js mentions (8)

  • Natural Language Processing (NLP) in JavaScript (series 2)
    We'll use the "natural" NLP library; follow the previous session to understand how to set up your environment. - Source: dev.to / almost 2 years ago
  • Natural Language Processing (NLP) in JavaScript (series)
    Several NLP libraries are available, each offering distinct features and functionalities. One popular choice in the JavaScript ecosystem is the Natural Language Toolkit for JavaScript (NLP.js), which provides a wide range of NLP capabilities. - Source: dev.to / almost 2 years ago
  • [AskJS] Rate a string on how much sense it makes
    For a JS based approach you could try NLP libraries like this one: https://github.com/axa-group/nlp.js. Source: about 2 years ago
  • The full tech stack to run a chatbot — behind the scenes of an open source bot platform
    To determine which chatbot intent is the best match for the user textual input, we rely on nlp.js (in JS) though we are in the process of moving to our new Python NLP server for better optimization of the needs of eCommerce conversations. A preprocessor language model is also used to improve the chances of a matching. - Source: dev.to / almost 3 years ago
  • How to build your own chatbot NLP engine
    Probably not. In fact, in Xatkit we aim to be a chatbot orchestration platform exactly to avoid reinventing the wheel and the non-invented here syndrome. So, in most cases, other existing platform (like DialogFlow or nlp.js) will work just fine. But we have also realized that there are always some particularly tricky bots for which you really need to be able to customize your engine to the specific chatbot... - Source: dev.to / about 3 years ago
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What are some alternatives?

When comparing Google Cloud Natural Language API and NLP.js, you can also consider the following products

Amazon Comprehend - Discover insights and relationships in text

NLTK - NLTK is a platform for building Python programs to work with human language data.

spaCy - spaCy is a library for advanced natural language processing in Python and Cython.

FuzzyWuzzy - FuzzyWuzzy is a Fuzzy String Matching in Python that uses Levenshtein Distance to calculate the differences between sequences.

Medallia - Medallia enables companies to capture customer feedback, understand it in real-time, and take action to improve the customer experience (CX).

Microsoft Bing Spell Check API - Enhance your apps with the Bing Spell Check API from Microsoft Azure. The spell check API corrects spelling mistakes as users are typing.