Augment human efforts to analyze unstructured text with AI using a variety of modeling approaches. Experience the combined power of natural language processing, machine learning and linguistic rules.
COVID-19 Scientific Literature Search & Text Analysis
Leveraging AI and a variety of modeling approaches, this free environment combines the power of natural language processing, machine learning, linguistic rules and network analytics – that you can access from a user-friendly visual interface.
Scale the human act of reading, organizing and extracting useful information from huge volumes of textual data.
Detect emerging trends and hidden opportunities.
Quickly and tirelessly sift through growing volumes of text data to identify main ideas or topics, extract key terms, analyze sentiment, and identify correlations between words with the right combination of natural language processing, machine learning and deep learning methods and linguistic rules. This helps get the right information to people when they need it.
Go from data to decisions faster.
Empower decision making at the source of the data, and reduce the gap between when information is received and when it is acted on. If someone leaves a comment or clicks through an app on a mobile device, SAS Visual Text Analytics analyzes the data immediately using in-memory, in-database and in-stream technologies. Embedded visualization capabilities allow for visual exploration of both data and analytics, while also providing intuitive dashboards that easily communicate results to a variety of stakeholders.
Foster collaboration and information sharing in an open ecosystem.
SAS Visual Text Analytics provides a flexible environment that supports the entire analytics life cycle – from data preparation, to discovering analytic insights, to putting models into production to realize value. Create, manage and share content, including best practice pipelines, in a highly collaborative workspace that easily integrates with existing systems and open source technology.
Improve analytic workflow with automation.
Intelligent algorithms and NLP techniques automatically detect relationships and sentiment in text data, eliminating time-consuming manual analysis. The use of human subject matter expertise to refine results is augmented with automatic rule generation and an interactive sandbox that allows you to evaluate subsets of rules to determine which ones are better performing. Drag and drop functionality, best practice templates, simple merge and split features, effortless topic promotion, automatic rule generation and one-click model deployment collectively reduce the human model building effort required, creating more time to focus on finding the information that matters.
Explore More on SAS® Visual Text Analytics & Beyond
Text Analytics for Executives
This paper looks at how organizations in banking, health care and life sciences, manufacturing and government are using SAS text analytics to drive better customer experiences, reduce fraud and improve society.
Text Analytics: Unlocking the Value of Unstructured Data
This research brief from the International Institute for Analytics and SAS outlines the challenges of implementing text analytics solutions and explores what makes this technology unique and exciting.
- Webinar Bring AI Capabilities to Life with Natural Language Processing and Text AnalyticsDiscover steps you can take to realize the promise of AI.
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