"Many Google teams provide pieces of the spam-protection puzzle, from distributed computing to language detection. For example, we use optical character recognition (OCR) developed by the Google Book Search team to protect Gmail users from image spam. And machine-learning algorithms developed to merge and rank large sets of Google search results allow us to combine hundreds of factors to classify spam," explains Google. "Gmail supports multiple authentication systems, including SPF (Sender Policy Framework), DomainKeys, and DKIM (DomainKeys Identified Mail), so we can be more certain that your mail is from who it says it's from. Also, unlike many other providers that automatically let through all mail from certain senders, making it possible for their messages to bypass spam filters, Gmail puts all senders through the same rigorous checks."
- Official Gmail Blog: How our spam filter works
- A Distributed Bayesian Spam Filtering using Hadoop Map/Reduce
- or Parallelizing Support Vector Machines on Distributed Computers
- Sender Reputation in a Large Webmail Service
- Spam Filtering using Google/GMAIL
Opening the black box of Deep Neural Networks via Information - https://arxiv.org/pdf/1703.00810.pdf 지금까지 딥 러닝은 어떻게 동작하는지 이해할 수 없다고 믿어져왔다...
음성 인공지능 분야에서 스타트업이 생각해볼 수 있는 전략은 아마 다음과 같이 3가지 정도가 있을 것이다: 독자적 Vertical 음성 인공지능 Application 구축 기 음성 플랫폼을 활용한 B2B2C 형태의 비지니스 구축 기 음성 플랫폼...
As mentioned ago, I've been forming up the Hamburg project with Hyunsik Choi. Let's see more detail in the diagram of computing met...