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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 Mobile Miner?

Experience streamlined hashing computations across multiple devices with Mobile Miner, a tool that continuously tracks and pinpoints the most lucrative mining prospects. In contrast to conventional mining programs that often necessitate intricate configurations and considerable trial and error, Mobile Miner offers a user-friendly approach that allows for cryptocurrency mining on virtually any device, including desktops. The cryptocurrency you mine is seamlessly transferred to a wallet under your control, which means you maintain absolute ownership over the wallet's access password. Protecting this password is vital, as it acts as the key to unlocking your mining rewards and managing your shares from the mining pool. By leveraging the capabilities of your home devices, Mobile Miner promotes cryptocurrency mining by utilizing their processing power to conduct crucial calculations that reinforce the decentralized framework of cryptocurrency. Over time, as you engage in this process, you will collect small increments of cryptocurrency, thus providing a manageable introduction to the realm of digital assets. Furthermore, Mobile Miner keeps users informed with the most current trends and profitability analyses in mining, significantly enhancing the overall user experience and enabling informed decision-making for future endeavors. This dynamic approach not only democratizes mining but also encourages more individuals to participate in the evolving landscape of cryptocurrency.

Media

Media

Integrations Supported

Bitcoin
Ethereum

Integrations Supported

Bitcoin
Ethereum

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Free
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

Mobile Miner

Company Website

mobileminer.org

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

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