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What is Watson Natural Language Understanding?

Watson Natural Language Understanding is a cloud-based solution that utilizes advanced deep learning methods to extract metadata from text, such as entities, keywords, categories, sentiment, emotions, relationships, and syntactic structures. Engage deeply with your data through text analysis, allowing for the extraction of keywords, concepts, categories, and beyond. This service can analyze unstructured data in more than thirteen different languages. With its pre-built machine learning models for text mining, it achieves an impressive level of accuracy in processing your content. You have the flexibility to deploy Watson Natural Language Understanding behind your firewall or on any preferred cloud platform. Tailor Watson to understand the unique language of your business and obtain customized insights through Watson Knowledge Studio. Your ownership of data is safeguarded, as we prioritize the security and confidentiality of your information, ensuring that IBM will not collect or retain your data. By leveraging our advanced natural language processing (NLP) tools, developers can effectively decipher and extract significant insights from their unstructured data, thereby improving their decision-making processes. This cutting-edge method not only simplifies data analysis but also empowers organizations to fully exploit their information resources, leading to better strategic outcomes. Organizations that embrace this technology are likely to see enhanced efficiency and innovation across their operations.

What is VizRefra?

Viztext provides a comprehensive approach to text analysis through its innovative 2D and 3D visual mapping capabilities, which include topic modeling, sentiment assessments, and word cloud generation. This distinctive machine learning algorithm facilitates the identification of themes within the analyzed text. By using interactive 2D and 3D maps, users can navigate through various topics effectively. The framework employs referential features to enable a coherent relational analysis of topics, complete with zoom-in and zoom-out functionalities and vibrant word clouds. Additionally, it evaluates the sentiment of the text through a pie chart that illustrates the proportions of positive, neutral, and negative sentiments. Visual representations also emphasize the key entities within the text by showcasing their respective percentages and highlights. Users can easily engage with the tool by dragging and dropping, uploading text files, or copying and pasting content from social media platforms. Alternatively, one can simply input a URL to analyze articles from specific websites, making it a versatile resource for text analysis.

Media

Media

Integrations Supported

TAS Insight Engine

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

$0.003 per NLU item
First 1-250,000 items
Free Version

Pricing Information

$25
30 days Free Trial will access the following:

- Text analysis package
- Limited to 30 articles/text upoads per day
- News monitor
- Twitter monitor

In addtion to the free trial option, the Pro User will have:

- Unlimited number of analysis and text uploads
- Unlimited support
- 24 hours responce time
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
Android
iPhone
iPad

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Not specified

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/cloud/watson-natural-language-understanding

Company Facts

Organization Name

VizRefra

Date Founded

2019

Company Location

Australia

Company Website

www.vizrefra.com

Categories and Features

Emotion Recognition

Not specified

Text Analytics

Not specified

Text Mining

Not specified

Categories and Features

Text Analytics

Not specified

Text Mining

Graphical Data Presentation
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

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