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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 Cauliflower?

Cauliflower is capable of processing feedback and comments related to all kinds of services or products. Utilizing Artificial Intelligence (AI), Cauliflower identifies key topics, assesses their significance, and establishes connections between them. It employs proprietary machine learning models designed to extract relevant content and gauge sentiment accurately. The platform features user-friendly dashboards equipped with filtering options and the ability to drill down into specific data points. Users can utilize various parameters to specify language, weight, ID, and timeframes. Additionally, custom filter variables can be defined from a dropdown menu. If needed, Cauliflower can translate its findings into a standardized language to ensure consistency. By adopting a company-wide language, businesses can move beyond sporadic readings of customer feedback and avoid simply quoting isolated opinions, thus fostering a more cohesive understanding of customer sentiment. This approach ultimately enhances strategic decision-making and improves overall customer engagement.

Media

Media

Integrations Supported

Amazon
Google Business Profile
Google Play
Tripadvisor
Trustpilot
Yelp

Integrations Supported

Amazon
Google Business Profile
Google Play
Tripadvisor
Trustpilot
Yelp

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

Cauliflower

Date Founded

2019

Company Location

Germany

Company Website

www.cauliflower.ai/

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

Artificial Intelligence

Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)

Customer Experience

Action Management
Analytics
Customer Segmentation
Dashboard
Feedback Management
Knowledge Management
Multi-Channel Collection
Sentiment Analysis
Survey Management
Text Analysis
Trend Analysis

Data Analysis

Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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

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