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Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? When used strategically, text-mining tools can transform raw data into real business intelligence , giving companies a competitive edge. How does text mining work?

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How process mining improves IT service management to save your business time and money

IBM Big Data Hub

For example, if a user’s email is down, they submit a ticket to IT. Similarly with ticket reopens: if a ticket is reopened after being resolved, it indicates the need to address an issue with training or IT resources. Process mining is an ideal solution to start planning for automation.

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3 new steps in the data mining process to ensure trustworthy AI

IBM Big Data Hub

Often the bias creeps in through training data and then is amplified and embedded in the model. To help data scientists reflect and identify possible ethical concerns the standard process for data mining should include 3 additional steps: data risk assessment, model risk assessment and production monitoring. Data risk assessment.

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How to unlock a scientific approach to change management with powerful data insights

IBM Big Data Hub

Grasping these opportunities at IBM, we’re increasingly building our specialism in process mining and data analysis tools and techniques we believe to be true ‘game changers’ when it comes to building cultures of continuous change and innovation. CoE = Center of Excellence = Accelerator for Change. Making it happen: Driving faster adoption.

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Adversarial ML Attack that Secretly Gives a Language Model a Point of View

Schneier on Security

Here’s the latest: a training-time attack that forces the model to exhibit a point of view: Spinning Language Models: Risks of Propaganda-As-A-Service and Countermeasures.” For example, a spinned summarization model outputs positive summaries of any text that mentions the name of some individual or organization.

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Attacks against machine learning — an overview

Elie

which involve feeding training adversarial data to the classifier. The most common attack type we observe is model skewing, where the attacker attempts to pollute training data in such a way that the boundary between what the classifier categorizes as good data, and what the classifier categorizes as bad, shifts in his favor.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.