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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 TextRazor?

The TextRazor API is a powerful tool designed to effectively reveal the Who, What, Why, and How of your news content. With features like Entity Extraction, Disambiguation, and Linking, it also includes Keyphrase Extraction, Automatic Topic Tagging, and Classification, supporting a total of twelve languages. This API conducts a thorough examination of your text, enabling the extraction of Relations, Typed Dependencies among words, and Synonyms, which aids in the creation of sophisticated semantic applications that are aware of context. Additionally, it facilitates the rapid extraction of custom entities such as products and companies, allowing users to set specific tagging rules that fit their content needs. TextRazor presents a flexible text analysis framework that can be accessed either through cloud services or by self-hosting. Its integration of advanced natural language processing technologies with a vast knowledge base helps users quickly generate valuable insights from various types of content, including documents, tweets, or web pages. This makes it a vital resource for both content creators and analysts who seek to enhance their understanding of data. Ultimately, TextRazor’s holistic approach guarantees that users can optimize their data processing and analytical strategies to achieve superior outcomes.

Media

Media

Integrations Supported

Neota
OpenResty
Pipedream
TiMi

Integrations Supported

Neota
OpenResty
Pipedream
TiMi

API Availability

Has API

API Availability

Has API

Pricing Information

$25
Free Trial Offered?
Free Version

Pricing Information

$200 per month
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

TextRazor

Date Founded

2011

Company Location

United Kingdom

Company Website

www.textrazor.com

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

Qualitative Data Analysis

Annotations
Collaboration
Data Visualization
Media Analytics
Mixed Methods Research
Multi-Language
Qualitative Comparative Analysis
Quantitative Content Analysis
Sentiment Analysis
Statistical Analysis
Text Analytics
User Research Analysis

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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