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Description
Utilize natural language processing to derive insights from unstructured text without needing machine learning expertise, leveraging a suite of features from Cognitive Service for Language. Enhance your comprehension of customer sentiments through sentiment analysis and pinpoint significant phrases and entities, including individuals, locations, and organizations, to identify prevalent themes and trends. Categorize medical terminology with specialized, pretrained models tailored for specific domains. Assess text in numerous languages and uncover vital concepts within the content, such as key phrases and named entities encompassing people, events, and organizations. Investigate customer feedback regarding your brand while analyzing sentiments related to particular subjects through opinion mining. Moreover, extract valuable insights from unstructured clinical documents like doctors' notes, electronic health records, and patient intake forms by employing text analytics designed for healthcare applications, ultimately improving patient care and decision-making processes.
Description
Language Understanding (LUIS) is an advanced machine learning service designed to incorporate natural language capabilities into applications, bots, and IoT devices. It allows for the rapid creation of tailored models that enhance over time, enabling the integration of natural language features into your applications. LUIS excels at discerning important information within dialogues by recognizing user intentions (intents) and extracting significant details from phrases (entities), all contributing to a sophisticated language understanding model. It works harmoniously with the Azure Bot Service, simplifying the process of developing a highly functional bot. With robust developer resources and customizable pre-existing applications alongside entity dictionaries such as Calendar, Music, and Devices, users can swiftly construct and implement solutions. These dictionaries are enriched by extensive web knowledge, offering billions of entries that aid in accurately identifying key insights from user interactions. Continuous improvement is achieved through active learning, which ensures that the quality of models keeps getting better over time, making LUIS an invaluable tool for modern application development. Ultimately, this service empowers developers to create rich, responsive experiences that enhance user engagement.
API Access
Has API
API Access
Has API
Integrations
Azure CLU
Azure Marketplace
BotCore
Dydu
Geomant
Geomant Wallboard
Ideta
Microsoft Entra ID
Neo Enterprise Assistant Platform
QnA Maker
Integrations
Azure CLU
Azure Marketplace
BotCore
Dydu
Geomant
Geomant Wallboard
Ideta
Microsoft Entra ID
Neo Enterprise Assistant Platform
QnA Maker
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
Microsoft
Founded
1975
Country
United States
Website
azure.microsoft.com/en-us/services/cognitive-services/text-analytics/
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
www.luis.ai/
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
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization
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