This data sheet offers a general overview of what we do, how we do it, and who we do it for, including our NLP features, products, deployment options, industries and applications, and more.
The Lexalytics Intelligence Platform is a complete business intelligence tool that includes all of the tools you need to gather, process, analyze and visualize text data in all its forms.
Learn how we help you solve precision or accuracy issues in your text analytics solution by tuning your system or training a machine learning "micromodel" to solve particularly tricky challenges.
Some documents contain structured data hidden in a seemingly unstructured format. For these cases, including PDFs and Word files, traditional analytics tools may fall short. Learn how Lexalytics can extract, organize and analyze this data.
Semantria wraps the text analytics and natural language processing features of our Salience engine into a flexible, easy-to-deploy RESTful API with graphical configuration tools.
See how our natural language processing and “words-first” machine learning combine in this overview of our full-stack business intelligence solution.
Learn how Lexalytics, a company with more than a decade of experience in the space, uses machine learning to solve tricky problems in natural language processing and text analytics.
We’ve developed a particular philosophy around how to customize a text analytics system to better fit your business. This white paper explains why you should "Tune First, Then Train".
Sentiment analysis is the process of determining whether a piece of writing is positive, negative or neutral. This paper dives deep into how it works, including the role of machine learning and AI.
What is sentiment scoring, and why should you care? This white paper outlines the basic of sentiment extraction in text analytics.
What are they talking about? Learn how we use natural language processing to categorize and sort comments, reviews and other text documents.
How does sentiment scoring work? This white paper details some of the methods we use to measure the emotional tone of text documents.
Context is the last frontier of text analytics. This white paper covers the complexities of getting a machine to think like a human, with a focus on Lexalytics' unique and powerful approach.
Who are they talking about? Learn how we extract people, places, dates, companies, products, jobs, and titles from text documents.
This white paper is a useful primer on the fundamentals and mechanisms of Natural Language Processing (NLP).
Here (by popular demand) is the ultimate Lexalytics tuning FAQ. Lexalytics Support Engineer Sarah Williams answers the user bases’ most popular questions. So, grab some coffee and a Trance playlist and dive right in.
In this research article, Chandra Shekhar Yadav explains why Lexalytics’ algorithm outperforms previous text document summarization methodologies.
What factors determine whether or not a brand’s Twitter content is shared among its audience? Luis Matosas López uses the Lexalytics Intelligence Platform to investigate these questions.
Our Semantria SaaS text analytics API can now be deployed wherever you need depending on your privacy, security and scalability requirements.
Machine learning micromodels reduce the challenges of sourcing and annotating data while delivering better precision and accuracy than macromodels.