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What is Leximancer?

Leximancer enhances your analytical abilities by automatically scrutinizing text documents to reveal significant concepts, offering vital ideas and actionable insights through comprehensive models, engaging visual representations, and user-friendly data exports. It supports various text formats and languages, making it ideal for both individual documents and extensive collections. By delving deeper than surface-level words, Leximancer uncovers the hidden narratives; text serves as a medium for ideas, concepts, and connections that might otherwise remain obscured. Rapidly pinpointing these concepts is essential for a complete understanding of the messages embedded in the text. This capability spans a diverse array of sources, such as customer surveys, published articles, interview transcripts, lengthy reports, web pages, feedback forms, tweets, and beyond, enabling you to grasp the true essence of the material. Importantly, Leximancer offers text modeling with minimal configuration, requiring no initial training sets or keyword lists, thereby mitigating human bias in the analytical process. Its strength lies in discovering concepts within their contextual framework rather than depending solely on keywords, producing timely results that significantly enhance your decision-making process. Moreover, the intuitive interface allows users to navigate complex data effortlessly, making it an indispensable tool for those seeking to unlock deeper insights from their text analysis endeavors.

What is Azure Text Analytics?

Harness natural language processing to gain valuable insights from unstructured text without requiring any machine learning knowledge, by utilizing an array of features from the Cognitive Services for Language. Elevate your understanding of customer emotions through sentiment analysis and identify key phrases and entities such as people, places, and organizations to uncover common themes and patterns. Use specialized, pretrained models to classify medical terminology specific to various fields. Evaluate text across multiple languages and reveal essential concepts within the content, which include key phrases and named entities that highlight individuals, events, and organizations. Delve into customer feedback regarding your brand while examining sentiments linked to specific topics through opinion mining techniques. Additionally, derive critical insights from unstructured clinical documents, including doctors' notes, electronic health records, and patient intake forms, by applying text analytics tailored for healthcare settings, ultimately enhancing patient care and informing decision-making processes. By integrating these advanced capabilities, organizations can stay ahead of trends and better meet the needs of their stakeholders.

Media

Media

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

Integrations Supported

Azure Marketplace
TAS Insight Engine
Unremot

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
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

Leximancer

Company Location

Australia

Company Website

info.leximancer.com

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/cognitive-services/text-analytics/

Categories and Features

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

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

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