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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 NetOwl TextMiner?

NetOwl TextMiner combines the renowned NetOwl Extractor with Elasticsearch to provide a cutting-edge text analytics platform. This software leverages the comprehensive capabilities of NetOwl, making it ideal for executing "what if" scenarios, engaging in discovery processes, supporting rapid investigations, and conducting in-depth research. By integrating all the text analytics tools from the NetOwl Extractor—such as entity extraction, relationship and event extraction, sentiment analysis, text categorization, and geotagging—TextMiner offers a robust text mining solution. The outcomes produced by the Extractor are efficiently stored within Elasticsearch, which enhances the system with a variety of intelligent search and analytical functions. The collaboration between Elasticsearch and NetOwl guarantees swift and scalable real-time text analysis, making it suitable for managing Big Data projects. Additionally, TextMiner features a user-friendly web interface that can be easily customized to meet diverse analytical requirements, allowing users to quickly extract the most pertinent insights from large text collections. This flexibility not only improves user experience but also facilitates more specialized analyses across different fields, catering to the unique needs of various industries.

Media

Media

Integrations Supported

ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SolrCommerce
Tableau

Integrations Supported

ArcGIS
Elasticsearch
Google Maps
IBM Cloud
Kibana
MarkLogic
Palantir Apollo
SolrCommerce
Tableau

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

NetOwl

Date Founded

1996

Company Location

United States

Company Website

www.netowl.com/text-mining

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

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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