from the large quantity of natural language data inundating the enterprise. Lexalytics is also launching a limited-availability beta release of Semantria Storage & Visualization, a content storage, aggregation, search and reporting framework that provides business analysts and marketers a single access point to interact with their data.
Lexalytics has been a pioneer in natural language processing (NLP) and text analytics, delivering the world’s first commercial sentiment analysis engine in 2004, the world’s first Twitter/microblog-specific text analytics in 2010 and the world’s first commercial semantic analytics based on Wikipedia in 2011. Lexalytics has experimented with tens of thousands of models to feed its text and sentiment analysis platforms, launching machine learning-based named entity extraction in 2008 and the world’s first unsupervised ML model for syntax analysis in 2014. The announcement is a direct result of years of internal research and development coupled with the work coming out of its Magic Machines™ AI Labs, a partnership among Lexalytics, the University of Massachusetts Amherst’s Center for Data Science and Northwestern University’s Medill School of Journalism, Media and Integrated Marketing Communications.
Lexalytics is the only vendor we’ve seen that can offer the flexibility that is required to support our complex product line,” said Csaba Dancshazy, senior market research manager, Microsoft. “We’re working closely with both their technology and services organizations to push the bounds of what can be accomplished with social data. They have contributed to methodology with their expertise, and have been creative and responsive in the development of features to meet our needs.”
AI Assembler Features
AI Assembler is an efficient pipeline for building machine learning-based, artificial intelligence applications for natural language processing. With AI Assembler, Lexalytics is now providing enterprise customers with the same tools to accomplish tasks like raising the accuracy of Named Entity Recognition by 25 percent in a fraction of the time it would take with standard industry technologies. AI Assembler includes:
- Multiple curated, machine learning algorithms ideal for analyzing a wide variety of text data, from short, jargon-filled tweets, to long, technical contracts and research papers;
- Fully automated hyperparameter optimization of the machine learning algorithms with the best research built-in, allowing for faster, more reliable and simpler model building;
- Operationalized AI incorporating standard processes (logging, undo/redo, maintenance of gold-standard test sets, structured maintenance and improvement of models, and rebuilding of independent models) to simplify, automate and enforce key procedural action items;
- The ML Builders team of Lexalytics data scientists and machine learning experts to assist with customers’ unique NLP challenges.
Semantria Storage & Visualization Features
Semantria Storage & Visualization gives customers a full-stack offering that connects Lexalytics’ existing products — AI Assembler, Semantria, Salience and Salience for Excel — with a flexible search and reporting framework. Semantria Storage & Visualization features:
- Rich filtering and search of processed content, enabling analysts to quickly sort out their desired content – great for running regular reporting or for custom analysis;
- Content storage and aggregation with the capability of storing billions of documents in one place;
- Reporting and graphical representations of data insights to enable sharing across teams and departments, including templates for Tableau and other leading BI platforms.
With our announcement, Lexalytics is pioneering the field of ‘words-first’ AI, offering our customers the same machine learning tools we use internally to power our text and sentiment analysis platforms, along with easy-to-use data storage and visualization tools to make the most of their data,” said Jeff Catlin, CEO of Lexalytics. “As data volumes continue to skyrocket and language continues to evolve, our customers have been asking for new ways to continue adding features while maintaining the accuracy they’ve come to expect from us: these new solutions are the answer.”
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