How Google’s Algorithm Rules the Web
This article illustrates the role of PageRank in Google’s algorithm, and the changes that they are constantly making to ensure that their search engine results are accurate in what the person may be looking for. Google’s algorithm started with PageRank, which rated pages based on the number and importance of links that pointed to them. It was this that Google credits their success as a search engine to. They first used PageRank to rank the millions of possible results and determine relevance by ensuring that the most useful ones show up at the top. However, Google has constantly worked to improve their search engine through utilizing many more signals, including documenting what words people replace in their query when they’re unsatisfied or what results they click on. This improves to relevance of their results as Google is able to learn more about the searchers and predict what they may be searching for. Google currently uses more than 200 signals to help rank its results, and continues to add more signals that keep up with human semantics and the rapid growth of the web. Overall, this article emphasizes the role of PageRank in Google’s algorithm, but also how they are able to build off PageRank to actively improve their search engine.
This relates to the concept of PageRank in lecture, in which nodes that are viewed as more important are ranked higher and get to make stronger endorsements. PageRank plays an important role in Google’s algorithm, as it formed the basis of their search engine and was first used to rank the possible results to determine which relevant pages were displayed at the top. However, this article also revealed some of the limitations of PageRank in terms of customization and human semantics, and how Google worked to make improvements to their search results through adding signals. Overall, this article demonstrates PageRank’s vital role in Google’s algorithm as it forms the basis of eliciting relevant content that a searcher may be looking for, and how it is able to be built upon to hone in on relevance and predicting what a searcher wants to see.
Link: https://www.wired.com/2010/02/ff_google_algorithm/