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Average Ratings 0 Ratings
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.
Description
The TextRazor API provides an efficient and precise means of uncovering the Who, What, Why, and How within your news articles. It features capabilities such as Entity Extraction, Disambiguation, and Linking, alongside Keyphrase Extraction, Automatic Topic Tagging, and Classification, supporting twelve different languages. This tool performs an in-depth analysis of your content, allowing for the extraction of Relations, Typed Dependencies between terms, and Synonyms, which empowers the development of advanced semantic applications that are context-aware. Furthermore, it enables the swift extraction of custom entities like products and companies, allowing users to create specific rules for tagging their content with personalized categories. TextRazor comprises a versatile text analysis infrastructure that can be utilized either via the cloud or through self-hosting. By integrating cutting-edge natural language processing techniques with an extensive repository of factual information, TextRazor aids in quickly deriving valuable insights from your documents, tweets, or web pages, making it an indispensable tool for content creators and analysts alike. This comprehensive approach ensures that users can maximize the effectiveness of their data processing and analysis efforts.
API Access
Has API
Yes
API Access
Has API
Yes
Integrations
.NET
Yes
C
Yes
C#
Yes
C++
Yes
Fleece AI
No
Java
Yes
Lexalytics
Yes
Neota
No
OpenResty
No
Pipedream
No
Integrations
.NET
No
C
No
C#
No
C++
No
Fleece AI
Yes
Java
No
Lexalytics
No
Neota
Yes
OpenResty
Yes
Pipedream
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$200 per month
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Lexalytics
Country
United States
Website
www.lexalytics.com/salience/
Vendor Details
Company Name
TextRazor
Founded
2011
Country
United Kingdom
Website
www.textrazor.com
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
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
Qualitative Data Analysis
Annotations
No
Collaboration
No
Data Visualization
No
Media Analytics
No
Mixed Methods Research
No
Multi-Language
No
Qualitative Comparative Analysis
No
Quantitative Content Analysis
No
Sentiment Analysis
No
Statistical Analysis
No
Text Analytics
No
User Research Analysis
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