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Google uses Machine Learning to Combat annoying ads in apps

The Google Play Store is a very open platform. Although this is a good thing for users and app developers, some “bad-hearted” people can load malicious programs or be annoying on the platform Ads to the software.

Google today announced that they have removed nearly 600 apps on the Play Store-and even banned them from monetizing AdMob and Ad Manager-because these delisted apps have repeatedly violated two advertising policies, including “Interfering ads” and “Disabled interstitial ads.

According to BuzzFeed News, the apps have been downloaded and installed more than 4.5 billion times.

Google defines disruptive ads as ads that affect device operation or ads that pop up on apps that users do n’t open often. For example, when a user unlocks their phone to make a call, an application may be triggered to place a full-screen ad and block the home screen.

Google uses Machine Learning

These pop-up ads not only affect the user ’s operating experience-eventually, but advertisers are also more likely to pay for the ad in vain. (Google says advertisers affected by this app removal will be refunded.)

Read: Google Removed ToTok from Play Store

           Google states that the Play Store uses a new machine-learning algorithm to detect relevant policies that apply to violations of distracting ads. This process helps the official to analyze and determine whether the developers and publishers are “recidivists.”

Per Bjorke, Google ’s senior product manager for ad traffic and quality revealed to BuzzFeed News that after they detect violations for the first time, they will issue notifications and warnings to developers and allow them to correct the problem. Officials will take tougher measures to deal with those who have broken the rules again.

For example, Cheetah Mobile, which had been in trouble for a long time, was eventually banned from entering the Play Store, and all of its apps were forced to be removed.

Encouragingly, Google is working to improve the Play Store experience. It is hoped that this machine learning strategy can block any applications with malicious programs and disruptive properties in the future to ensure that users’ devices are protected from infections and attacks.

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