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Description
CATMA is an innovative web platform designed for text annotation, analysis, and visualization, tailored to replicate the adaptable processes of hermeneutic text interpretation. Users can engage with the application in a manner that aligns best with their research objectives, whether they prefer qualitative or quantitative methods, exploratory approaches, or a more structured, taxonomy-driven analysis, allowing for both individual and collaborative efforts. The latest iteration, Version 6, introduces a host of new functionalities, with its framework now organized around distinct projects. These projects can encompass various elements, including Documents, Annotations, Tagsets, and Members, enhancing the organization of collaborative annotation through updated roles-and-rights management features. Improvements to analysis capabilities include refined query options and visualizations that are seamlessly integrated, alongside a collection of standard queries and fresh visualization tools. Furthermore, the user interface has undergone a comprehensive redesign, resulting in a more streamlined and user-friendly experience that enhances overall usability. With these advancements, CATMA continues to support diverse research needs while making the process of text analysis more accessible and efficient.
Description
The TextRazor API provides an efficient and precise means of uncovering the Who, What, Why, and How within your news articles. It features capabilities such as Entity Extraction, Disambiguation, and Linking, alongside Keyphrase Extraction, Automatic Topic Tagging, and Classification, supporting twelve different languages. This tool performs an in-depth analysis of your content, allowing for the extraction of Relations, Typed Dependencies between terms, and Synonyms, which empowers the development of advanced semantic applications that are context-aware. Furthermore, it enables the swift extraction of custom entities like products and companies, allowing users to create specific rules for tagging their content with personalized categories. TextRazor comprises a versatile text analysis infrastructure that can be utilized either via the cloud or through self-hosting. By integrating cutting-edge natural language processing techniques with an extensive repository of factual information, TextRazor aids in quickly deriving valuable insights from your documents, tweets, or web pages, making it an indispensable tool for content creators and analysts alike. This comprehensive approach ensures that users can maximize the effectiveness of their data processing and analysis efforts.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
Fleece AI
No
Neota
No
OpenResty
No
Pipedream
No
TIMi
No
Integrations
Fleece AI
Yes
Neota
Yes
OpenResty
Yes
Pipedream
Yes
TIMi
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Pricing Details
$200 per month
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
CATMA
Founded
2009
Country
Germany
Website
catma.de/
Vendor Details
Company Name
TextRazor
Founded
2011
Country
United Kingdom
Website
www.textrazor.com
Product Features
Qualitative Data Analysis
Annotations
Yes
Collaboration
Yes
Data Visualization
Yes
Media Analytics
No
Mixed Methods Research
No
Multi-Language
Yes
Qualitative Comparative Analysis
No
Quantitative Content Analysis
No
Sentiment Analysis
No
Statistical Analysis
Yes
Text Analytics
Yes
User Research Analysis
No
Product Features
Natural Language Processing
Co-Reference Resolution
No
In-Database Text Analytics
No
Named Entity Recognition
No
Natural Language Generation (NLG)
No
Open Source Integrations
No
Parsing
No
Part-of-Speech Tagging
No
Sentence Segmentation
No
Stemming/Lemmatization
No
Tokenization
No
Qualitative Data Analysis
Annotations
No
Collaboration
No
Data Visualization
No
Media Analytics
No
Mixed Methods Research
No
Multi-Language
No
Qualitative Comparative Analysis
No
Quantitative Content Analysis
No
Sentiment Analysis
No
Statistical Analysis
No
Text Analytics
No
User Research Analysis
No
Text Mining
Boolean Queries
No
Document Filtering
No
Graphical Data Presentation
No
Language Detection
No
Predictive Modeling
No
Sentiment Analysis
No
Summarization
No
Tagging
No
Taxonomy Classification
No
Text Analysis
No
Topic Clustering
No
