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What is SAS Text Miner?

SAS Text Miner facilitates the extraction of valuable insights from diverse text documents, uncovering hidden themes and concepts. This tool adeptly combines quantitative information with unstructured text, effectively blending text mining with traditional data mining techniques. Being a part of the SAS® Enterprise Miner suite, it requires that SAS Enterprise Miner is installed on the same system to function properly. Furthermore, SAS High-Performance Text Mining can run on both a grid of computers or a single machine with multiple CPUs, making it flexible for various computing environments. The text algorithms used are optimized for multi-threading and operate in memory, which greatly improves both speed and efficiency while reducing input/output load. Users can access SAS Text Miner as nodes within the SAS High-Performance Data Mining framework or through the procedures PROC HPTMINE and PROC HPTMSCORE. To better understand SAS technology, individuals can take advantage of training courses provided by analytics experts, which will help them attain a thorough grasp of the available tools. Gaining expertise in these areas not only boosts one’s analytical skills but also enhances overall capabilities in data mining and analysis methodologies. Ultimately, mastering these techniques can empower users to make more informed decisions based on data-driven insights.

What is InfoNgen?

InfoNgen serves as an advanced text analytics and sentiment analysis platform that efficiently reveals actionable insights from vast amounts of information. By streamlining the process of making strategic decisions, teams can focus on sharing, analyzing, and disseminating only the most essential insights derived from both structured and unstructured data. With its innovative tools for sentiment analysis and text mining, InfoNgen enables users to identify significant patterns, trends, and anomalies within their datasets. Unlike other solutions, InfoNgen uniquely integrates its specialized use cases with robust functionalities, thereby enhancing decision-making capabilities for employees and accelerating their workflow. This powerful platform acts as a vital asset for businesses seeking to locate critical information quickly, featuring pre-built industry taxonomies alongside customizable delivery options to meet diverse needs. Consequently, organizations can leverage InfoNgen not only to improve efficiency but also to stay ahead in a competitive landscape.

Media

Media

Integrations Supported

AWS Elemental
Dropbox
Google Cloud Document AI
Microsoft OneDrive
Microsoft SharePoint
Microsoft Teams
Salesforce

Integrations Supported

AWS Elemental
Dropbox
Google Cloud Document AI
Microsoft OneDrive
Microsoft SharePoint
Microsoft Teams
Salesforce

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

SAS Institute

Date Founded

1976

Company Location

United States

Company Website

support.sas.com/en/software/text-miner-support.html

Company Facts

Organization Name

EPAM Systems

Company Location

United States

Company Website

www.epam.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

Enterprise Search

AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery

Insight Engines

AI / Machine Learning
Augmented Analytics
Data Aggregation
Data Classification
Data Extraction
Data Source Connectors
Full Text Search
Intent Recognition
Multiple Data Sources
Search / Filter
Sentiment Analysis

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