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What is Watson Natural Language Understanding?

Watson Natural Language Understanding is a cloud-based solution that utilizes advanced deep learning methods to extract metadata from text, such as entities, keywords, categories, sentiment, emotions, relationships, and syntactic structures. Engage deeply with your data through text analysis, allowing for the extraction of keywords, concepts, categories, and beyond. This service can analyze unstructured data in more than thirteen different languages. With its pre-built machine learning models for text mining, it achieves an impressive level of accuracy in processing your content. You have the flexibility to deploy Watson Natural Language Understanding behind your firewall or on any preferred cloud platform. Tailor Watson to understand the unique language of your business and obtain customized insights through Watson Knowledge Studio. Your ownership of data is safeguarded, as we prioritize the security and confidentiality of your information, ensuring that IBM will not collect or retain your data. By leveraging our advanced natural language processing (NLP) tools, developers can effectively decipher and extract significant insights from their unstructured data, thereby improving their decision-making processes. This cutting-edge method not only simplifies data analysis but also empowers organizations to fully exploit their information resources, leading to better strategic outcomes. Organizations that embrace this technology are likely to see enhanced efficiency and innovation across their operations.

What is Hyland Document Filters?

Discover what firms like Cisco, Reveal Data, and Absolute Software have learned about Catalyst and similar products! Document Filters serves as an essential toolkit for facilitating file inspection and processing capabilities within applications for eDiscovery, data loss prevention, text analysis, and content management. It empowers users to search through, archive, and retrieve files efficiently. Are your users overwhelmed by the variety of file formats and the sheer volume of documents? We delve into how Document Filters enhances efficiency and delivers customer value, significantly benefiting all users in the process. Furthermore, Document Filters enables software developers to embed top-tier file identification features into their applications. By utilizing intelligent file identification, Document Filters effectively analyzes source content without solely depending on the filename extension, ensuring more accurate processing. This innovative approach not only streamlines workflows but also elevates the overall user experience.

Media

Media

Integrations Supported

.NET
C
C#
C++
Hyland RPA
Java
Python
TAS Insight Engine

Integrations Supported

.NET
C
C#
C++
Hyland RPA
Java
Python
TAS Insight Engine

API Availability

Has API

API Availability

Has API

Pricing Information

$0.003 per NLU item
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

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/cloud/watson-natural-language-understanding

Company Facts

Organization Name

Hyland Software

Date Founded

1991

Company Location

United States

Company Website

www.hyland.com/en/solutions/products/document-filters

Categories and Features

Emotion Recognition

Facial Emotions
Facial Expression Analysis
Machine Learning
Photo Emotions
Speech Emotions
Video Emotions
Written Text Emotions

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

Categories and Features

Document Management

Access Controls
Archiving & Retention
Collaboration Tools
Compliance Tracking
Document Archiving
Document Assembly
Document Capture
Document Conversion
Document Delivery
Document Indexing
Document Retention
Electronic Signature
Email Management
File Recovery
File Type Conversion
Forms Management
Full Text Search
Offline Access
Optical Character Recognition
Print Management
Version Control

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