Smartlogic News
The Latest Trends, Insight, and Information

Articles

Smartlogic Sponsors - Denver Federal Center Technology Day

on: May 17, 2019, by: Ann Kelly

Join us at FBC’s 21st Annual Technology Day at Denver Federal Center on June 13th. We’ll be in the DFC, building 25 lecture hall in Lakewood Colorado

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Articles

Smartlogic to Sponsor JWG RegTech Capital Markets Conference

on: May 13, 2019, by: Ann Kelly

Smartlogic sponsors JWG RegTech Capital Markets Conference. Now in its 4th year, the JWG RegTech conference will explore the cracks in public and private sector capabilities, disconnects between change programs and BAU compliance, and the latest thinking on how to best manage skyrocketing regulatory noise levels.

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Articles

Licensing a Taxonomy or Ontology

on: December 04, 2018, by: Ann Kelly

Smartlogic guest blogger Heather Hedden from Cengage takes us through the reasons, pros, and cons of licensing a taxonomy/ontology.

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Smartlogic is off to the races as sponsor for Sahlen’s Six Hours of the Glen on July 1st, 2018

on: June 25, 2018, by: Ann Kelly

Smartlogic is excited to announce their partnership with the JDC-Miller MotorSports racing team and their driver, Nelson Panciatici, as a sponsor for this year’s Sahlen’s Six Hours of the Glen at the Watkins Glen Raceway in New York - on their #85 racing car.

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Smartlogic Named by KMWorld as ‘One of the 100 Companies that Matter in Knowledge Management’ 2018

on: March 08, 2018, by: Ann Kelly

Smartlogic, the leader in Enterprise Intelligence solutions, has been named as one of KMWorld’s 100 Companies That Matter in Knowledge Management.

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Articles

Can the CDC use Twitter, AI and Google to forecast flu outbreaks?

on: September 25, 2017, by: Ann Kelly

Epidemiological forecasting, much like weather forecasting, may be able to bring together volumes of data – from retail sales of flu medications, to Google searches about flu symptoms, to tweets about symptoms or how someone might be feeling – to create a picture in near real-time that predicts the best possible picture of the spread of the virus. If it’s successful, predicting the spread of disease will be as commonplace as predicting rain or snow.

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Articles

A solid information strategy with Semaphore

on: August 15, 2017, by: Ann Kelly

The cornerstone to a solid information strategy is the ability to retain the information you need, discard what you don’t and provide all stakeholders within the enterprise the information they require. Knowing what information exists in the enterprise is key to protecting intellectual property and minimizing exposure to risk.

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Articles

Classification - powerful enrichment with Semaphore

on: July 20, 2017, by: Ann Kelly

Semaphore facilitates the development of semantic models, which are used to create a set of classification rule-bases, that automatically analyze and tag information assets. With Semaphore, organizations benefit from the complete and consistent application of quality metadata across all information repositories without imposing manual processes on their users.

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Articles

Semaphore and Adobe Experience Manager improve the user experience with metadata

on: June 27, 2017, by: Ann Kelly

Creating content, attracting and engaging customers and delivering personalized experiences as effectively as possible requires comprehensive metadata. That’s why many organizations choose to connect Smartlogic’s Semaphore platform to Adobe Experience Manager (AEM). The Semaphore platform harmonizes all vocabularies across the enterprise into a model that is leveraged and combined with sophisticated semantic strategies to classify assets and apply rich metadata. The integration of metadata into AEM results in a highly relevant navigation and discovery experience for users.

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Articles

Machine Learning and AI in Property and Casualty insurance

on: June 16, 2017, by: Ann Kelly

In Property and Casualty Insurance, information is the currency that drives pricing, claim loss prediction and prevention, risk management and customer experience. AXA, a global insurance company, created a proof of concept (POC) using machine learning to optimize pricing by predicting “large-loss” traffic accidents with 78% accuracy.

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