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Description
SAS Text Miner allows for the extraction of insights from a variety of text documents, revealing underlying themes and concepts. This tool effectively integrates quantitative data with unstructured text, merging text mining with conventional data mining approaches. As part of the SAS® Enterprise Miner suite, it necessitates that SAS Enterprise Miner is installed on the same system. Additionally, SAS High-Performance Text Mining can operate on either a computer grid or a single machine equipped with multiple CPUs. The text algorithms employed are designed to be multi-threaded and work in-memory, significantly enhancing both responsiveness and concurrency while minimizing input/output strain. Users can access SAS Text Miner as nodes within the SAS High-Performance Data Mining framework or utilize it through the procedures PROC HPTMINE and PROC HPTMSCORE. To quickly grasp SAS technology, individuals can benefit from courses offered by analytics professionals, ensuring they gain a comprehensive understanding of the tools available. Enhancing one’s knowledge in this area can lead to greater proficiency in data analysis and mining techniques.
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
API Access
Has API
Integrations
Fleece AI
Neota
OpenResty
Pipedream
TiMi
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$200 per month
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
SAS Institute
Founded
1976
Country
United States
Website
support.sas.com/en/software/text-miner-support.html
Vendor Details
Company Name
TextRazor
Founded
2011
Country
United Kingdom
Website
www.textrazor.com
Product Features
Text Mining
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering
Product 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
