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Average Ratings 0 Ratings
Description
Incorporate our advanced text analytics APIs to infuse your product, platform, or application with state-of-the-art natural language processing capabilities. Boasting the most comprehensive NLP feature set available, our technology has been refined over 19 years and is continually updated with new libraries, configurations, and models. You can assess whether a written piece conveys a positive, negative, or neutral sentiment, as well as sort and categorize documents into tailored groups. Additionally, our system can identify the expressed intentions of customers and reviewers, and extract pertinent information such as people, locations, dates, companies, products, jobs, and titles. You have the flexibility to deploy our text analytics and NLP solutions across a variety of infrastructures, including on-premise, private cloud, hybrid cloud, and public cloud environments. Our foundational software libraries for text analytics and natural language processing are fully accessible and at your service. This offering is especially advantageous for data scientists and architects who seek unrestricted access to the core technology or require on-premise deployment to maintain security and privacy standards. Ultimately, our innovative solutions empower you to harness the full potential of language data effectively.
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.
API Access
Has API
API Access
Has API
Integrations
.NET
Altair Activate
C#
CisionOne
DataSift
Hootsuite
Microsoft 365
PubNub
Python
Salience
Integrations
.NET
Altair Activate
C#
CisionOne
DataSift
Hootsuite
Microsoft 365
PubNub
Python
Salience
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Lexalytics
Country
United States
Website
www.lexalytics.com
Vendor Details
Company Name
SAS Institute
Founded
1976
Country
United States
Website
support.sas.com/en/software/text-miner-support.html
Product Features
Natural Language Processing
Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization
Text Mining
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering
Product Features
Text Mining
Boolean Queries
Document Filtering
Graphical Data Presentation
Language Detection
Predictive Modeling
Sentiment Analysis
Summarization
Tagging
Taxonomy Classification
Text Analysis
Topic Clustering