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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.

What is Salience?

Delve into the powerful features of text analytics and natural language processing (NLP) software libraries that can be installed on-site or seamlessly integrated into existing systems. Salience can be embedded within your enterprise business intelligence framework or adapted to suit your specific data analytics requirements. Capable of processing up to 200 tweets per second, Salience efficiently scales from single-core setups to large-scale data center environments, all while keeping a minimal memory footprint. Users can choose from bindings in Java, Python, or .NET/C# for easy integration, or utilize the native C/C++ interface to achieve optimal performance. This platform grants you extensive control over the underlying technology, enabling precise adjustments to various aspects of text analytics and NLP tasks such as tokenization, part-of-speech tagging, sentiment detection, categorization, and thematic analysis. Designed around a pipeline model that incorporates NLP rules and machine learning algorithms, it allows for straightforward identification of process issues. You can adjust particular features without compromising the system's overall stability. Furthermore, Salience operates entirely on your servers, yet it is flexible enough to allow for the transfer of non-sensitive data to cloud platforms, striking a balance between security and adaptability for your analytics operations. This versatility not only enhances the organization’s ability to utilize sophisticated analytics capabilities but also prioritizes data privacy and operational efficiency, ensuring that businesses can achieve their analytical goals without sacrificing security. By leveraging these capabilities, organizations can stay ahead in their data-driven decision-making processes.

Media

Media

Integrations Supported

.NET
C
C#
C++
Java
Lexalytics
Python
Semantria

Integrations Supported

.NET
C
C#
C++
Java
Lexalytics
Python
Semantria

API Availability

Has API

API Availability

Has API

Pricing Information

$25
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

VizRefra

Date Founded

2019

Company Location

Australia

Company Website

www.vizrefra.com

Company Facts

Organization Name

Lexalytics

Company Location

United States

Company Website

www.lexalytics.com/salience/

Categories and Features

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

Categories and Features

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Text Mining

Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering

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