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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
Explore the capabilities of text analytics and NLP software libraries that can be deployed on-premise or integrated seamlessly into your systems. You can incorporate Salience into your enterprise business intelligence framework or even customize it for your own data analytics solutions. With the ability to handle up to 200 tweets per second, Salience efficiently scales from individual cores to extensive data center infrastructures while maintaining a compact memory footprint. Choose from Java, Python, or .NET/C# bindings for user-friendly integration, or opt for the native C/C++ interface to achieve peak performance. Gain comprehensive control over the foundational technology, allowing you to fine-tune every aspect of text analytics and NLP functions, including tokenization, part of speech tagging, sentiment analysis, categorization, and thematic exploration. The platform is designed around a pipeline model consisting of NLP rules and machine learning algorithms, enabling you to pinpoint issues in the process easily. You can modify specific features without affecting the overall system's integrity. Moreover, Salience operates entirely on your own servers while remaining adaptable enough to transfer non-sensitive data to cloud environments, offering both security and versatility for your analytics needs. This flexibility empowers organizations to leverage advanced analytics features while ensuring data privacy and performance efficiency.
API Access
Has API
No
API Access
Has API
Yes
Integrations
.NET
No
C
No
C#
No
C++
No
Java
No
Lexalytics
No
Python
No
Semantria
No
Integrations
.NET
Yes
C
Yes
C#
Yes
C++
Yes
Java
Yes
Lexalytics
Yes
Python
Yes
Semantria
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
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
Yes
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
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
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
Lexalytics
Country
United States
Website
www.lexalytics.com/salience/
Product Features
Text Mining
Boolean Queries
Yes
Document Filtering
Yes
Graphical Data Presentation
No
Language Detection
Yes
Predictive Modeling
Yes
Sentiment Analysis
Yes
Summarization
No
Tagging
No
Taxonomy Classification
Yes
Text Analysis
No
Topic Clustering
Yes
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
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
