HubSpot Inbound Marketing Practice Exam

What is Google's machine-learning system that interprets searches to find relevant pages?

1. BERT

2. RankBrain

3. Hummingbird

4. Penguin

The correct answer is: RankBrain

RankBrain is the correct answer because it is a component of Google's overall search algorithm that specifically uses machine learning to understand and interpret the nuances of search queries. Introduced in 2015, RankBrain helps Google process search results more effectively by interpreting the intent behind users' queries and finding relevant pages that match that intent—even when the exact terms used in a search are not present on the relevant pages. This system significantly improves search results by allowing Google to understand the context of words and phrases, which is crucial for handling complex queries and providing users with the most pertinent information available. Instead of solely relying on matching keywords, RankBrain is able to consider various factors, including synonyms and the overall meaning of a query. Other options, while related to Google's search technology, serve different purposes. For example, BERT is another machine learning model that aids in understanding the context of words in search queries, but it was introduced later than RankBrain. Hummingbird refers to a complete overhaul of Google's search algorithm that focuses on understanding searches and providing more relevant results overall. Penguin is aimed at identifying and penalizing sites that violate Google's quality guidelines, specifically in regard to link schemes and spamming practices. Each of these plays a different role in the broader search ecosystem,