How DataScava’s Intelligent Approach Adds Value to Unstructured Data

Check out this article written by our CTO John Harney about how DataScava mines unstructured textual data using our Non-Semantic Domain-Specific Parser and patented “Weighted Topic Scoring”:

“Real-time mining of unstructured textual content isn’t simple. Available solutions don’t work well unless they’re fine-tuned to meet your specific needs and address the unique quirks in your company’s information. To truly add value, your applications, whether AI-driven or not, require a vocabulary that captures the definitions, context and nuance of your business.

“DataScava’s unstructured data miner provides fast and effective solutions for leveraging the explosive growth of unstructured data. The sheer volume of information—even some small businesses must manage thousands of pages each day—challenges companies to find the most efficient and accurate way to read data, index it, extract what they need and quickly route it to its proper destination.

“Conventional wisdom says that taking full advantage of information requires a “data-driven system” based on “artificial intelligence, “machine learning” or some other application. But without modification, these technologies often process information quickly, but incorrectly. Needless to say, machines that use inaccurate data for machine learning, AI insights, business decisions, or that pass data to the wrong destination, don’t do anyone much good.

“That’s where DataScava comes in.” Read the full article here.