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Description

Collaborative text analytics for machine-learning and human. We offer a variety of multilingual, text mining and data science features, as well as human annotation and machine-learning capabilities. DiscoverText provides a variety of cloud-based software tools that allow users to quickly and accurately analyze large amounts of text data. Our customers use DiscoverText to sort unstructured text commonly found in market research. They also include associated metadata such as customer feedback platforms, CRMs and chats. Discover why we are ranked #1 in text, metadata, social network analysis support, and trusted by hundreds academic research groups. Machine-learning sifters can be created in just hours or minutes by crowdsourcing. We provide an API and support technical integrations to SurveyMonkey and Twitter.

Description

Explore the capabilities of text analytics and NLP software libraries that can be deployed on-premise or integrated seamlessly into your systems. You can incorporate Salience into your enterprise business intelligence framework or even customize it for your own data analytics solutions. With the ability to handle up to 200 tweets per second, Salience efficiently scales from individual cores to extensive data center infrastructures while maintaining a compact memory footprint. Choose from Java, Python, or .NET/C# bindings for user-friendly integration, or opt for the native C/C++ interface to achieve peak performance. Gain comprehensive control over the foundational technology, allowing you to fine-tune every aspect of text analytics and NLP functions, including tokenization, part of speech tagging, sentiment analysis, categorization, and thematic exploration. The platform is designed around a pipeline model consisting of NLP rules and machine learning algorithms, enabling you to pinpoint issues in the process easily. You can modify specific features without affecting the overall system's integrity. Moreover, Salience operates entirely on your own servers while remaining adaptable enough to transfer non-sensitive data to cloud environments, offering both security and versatility for your analytics needs. This flexibility empowers organizations to leverage advanced analytics features while ensuring data privacy and performance efficiency.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

.NET No 
C No 
C# No 
C++ No 
Java No 
Lexalytics No 
Python No 
Semantria No 
SurveyMonkey Yes 
WordPress Yes 
X (Twitter) Yes 

Integrations

.NET Yes 
C Yes 
C# Yes 
C++ Yes 
Java Yes 
Lexalytics Yes 
Python Yes 
Semantria Yes 
SurveyMonkey No 
WordPress No 
X (Twitter) No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs No 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

Texifter

Founded

2009

Country

United States

Website

discovertext.com

Vendor Details

Company Name

Lexalytics

Country

United States

Website

www.lexalytics.com/salience/

Product Features

Text Mining

Boolean Queries Yes 
Document Filtering Yes 
Graphical Data Presentation Yes 
Language Detection Yes 
Predictive Modeling Yes 
Sentiment Analysis Yes 
Summarization No 
Tagging Yes 
Taxonomy Classification Yes 
Text Analysis Yes 
Topic Clustering No 

Product Features

Natural Language Processing

Co-Reference Resolution No 
In-Database Text Analytics No 
Named Entity Recognition No 
Natural Language Generation (NLG) No 
Open Source Integrations No 
Parsing No 
Part-of-Speech Tagging No 
Sentence Segmentation No 
Stemming/Lemmatization No 
Tokenization No 

Text Mining

Boolean Queries No 
Document Filtering No 
Graphical Data Presentation No 
Language Detection No 
Predictive Modeling No 
Sentiment Analysis No 
Summarization No 
Tagging No 
Taxonomy Classification No 
Text Analysis No 
Topic Clustering No 

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