Category: Big Data and Entity Analytics
Entity Graphs with Novetta Entity Analytics and Amazon Neptune
When extracting value from data, organizations often encounter challenges such as datasets of varying schemas, large volumes of data, and missing unique identifiers which enable entity linking. Novetta ...
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Enriching Entities In Your Data Lake
Overview Many of our customers have incredible amounts of data scattered across their organization. They know hidden information is locked away, but they need ways to integrate that ...
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Deploying Machine Learning at the Edge
From the team that presented AWS re:Invent 2018 session WPS304 “Rapid Prototyping for Today’s Mission”. Problem It’s imperative for warfighters to have actionable, up-to-date knowledge about their adversaries ...
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Novetta has BIG PLANS for AWS re:Invent 2018
Novetta is excited to return to one of the world’s largest tech conferences, AWS re:Invent! This year there are even more ways to engage with us in Las ...
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NLP Transfer Learning on SageMaker
Novetta Machine Learning Center of Excellence effort to develop a deep learning model that predicts customer-relevant metadata tags for unstructured text. BACKGROUND: ENRICHMENT OF UNSTRUCTURED TEXT DATA The ...
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Named Entity Recognition and Graph Visualization
PHASE I RECAP We are exploring the problem space of Named Entity Recognition (NER): processing unannotated text and extracting people, locations, and organizations. A previous post described our comparative ...
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Evaluating Solutions for Named Entity Recognition
BACKGROUND Named Entity Recognition (NER) and Entity Extraction are interchangeable terms that refer to the task of classifying “named entities” into pre-defined categories such as the names of ...
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Accelerating OSINT Analytics through AWS Machine Learning Services & AWS Neptune
by Matt Johannessen Novetta’s business covers a diverse mix of public and private sector customers. While mission objectives vary, we are seeing an increasing need to extract meaning ...
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