Blog 2018-07-03T17:33:00+00:00

Blog

Company Update

DataVisor’s David Ting: How AI Technology Can Improve the ROIs of Acquiring New Users

The 16th ChinaJoy kicked off in Shanghai, China on August 3, 2018. The Global Game Industry Summit was held concurrently. David Ting, Vice President of Engineering from DataVisor, gave a speech titled “How AI Technology Can Improve the ROIs of Acquiring New Users” where he discussed the fake app install problems and introduced DataVisor’s fraud detection technology for the mobile gaming industry.

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Quick Take

Maximizing User Acquisition ROI with AI Technology

In recent years, many mobile applications, including mobile games, have expanded to the global market. However, as they expand, fake traffic is becoming a growing problem that has long plagued many game developers. It directly results in the waste of marketing resources, making it impossible for developers to have real control over the ROIs of acquiring new users. 

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Company Update

Announcing the Q1 2018 DataVisor Fraud Index Report

The DataVisor report provides the latest insights into trends in global fraud activity and attack techniques. Last quarter, we uncovered a total of 900 million malicious activities and transactions. The report reveals dramatic growth in fraud infrastructure, with fraudulent accounts growing by 50% from Q4 2017 to Q1 2018.

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Technical Post

Technical Blog | Are Labels Useful to Unsupervised Algorithms?

Does the fact that UML doesn’t require labels mean that there is no benefit at all to labels? If label data exists already, how can it be used to improve UML detection results? In this article we discuss how labels can be effectively used in UML detection, even if they are not required.

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Unsupervised Machine Learning Cat B
Quick Take

Unsupervised Machine Learning: A 5-Minute Beginner’s Guide

Unsupervised Machine Learning (UML) is a topic that we get a lot of questions about here at DataVisor, because UML is at the core of our detection platform. In this 5-minute primer on UML, we start by defining the overarching field of Artificial Intelligence, then we drill down to the sub-field of Machine Learning, and lastly we discuss the various machine learning techniques, including UML, and when each ML technique is most effective.

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