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2. PageRank - Wikipedia

   en.wikipedia.org/wiki/PageRank

   PageRank (PR) is an algorithm used by Google Search to rank web pages in their search engine results. It is named after both the term "web page" and co-founder Larry Page. PageRank is a way of measuring the importance of website pages. According to Google:

3. Search engine optimization metrics - Wikipedia

   en.wikipedia.org/wiki/Search_engine_optimization...

   Google PageRank (Google PR) is one of the methods Google uses to determine a page's relevance or importance. Important pages receive a higher PageRank and are more likely to appear at the top of the search results. Google PageRank (PR) is a measure from 0 - 10. Google PageRank is based on backlinks.

4. Google Search - Wikipedia

   en.wikipedia.org/wiki/Google_Search

   Google Search uses algorithms to analyze and rank websites based on their relevance to the search query. It is the most popular search engine worldwide. Google Search is the most-visited website in the world. As of 2020, Google Search has a 92% share of the global search engine market. [3]

5. Search engine optimization - Wikipedia

   en.wikipedia.org/wiki/Search_engine_optimization

   Search engine optimization (SEO) is the process of improving the quality and quantity of website traffic to a website or a web page from search engines. [1] [2] SEO targets unpaid search traffic (usually referred to as "organic" results) rather than direct traffic, referral traffic, social media traffic, or paid traffic.

6. Ranking (information retrieval) - Wikipedia

   en.wikipedia.org/wiki/Ranking_(information...

   Ranking of query is one of the fundamental problems in information retrieval (IR), [1] the scientific/engineering discipline behind search engines. [2] Given a query q and a collection D of documents that match the query, the problem is to rank, that is, sort, the documents in D according to some criterion so that the "best" results appear early in the result list displayed to the user.

7. Discounted cumulative gain - Wikipedia

   en.wikipedia.org/wiki/Discounted_cumulative_gain

   The nDCG values for all queries can be averaged to obtain a measure of the average performance of a search engine's ranking algorithm. Note that in a perfect ranking algorithm, the will be the same as the producing an nDCG of 1.0. All nDCG calculations are then relative values on the interval 0.0 to 1.0 and so are cross-query comparable.