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  2. Search engine optimization - Wikipedia

    en.wikipedia.org/wiki/Search_engine_optimization

    The 2012 Google Penguin attempted to penalize websites that used manipulative techniques to improve their rankings on the search engine. [30] Although Google Penguin has been presented as an algorithm aimed at fighting web spam, it really focuses on spammy links [ 31 ] by gauging the quality of the sites the links are coming from.

  3. Google Panda - Wikipedia

    en.wikipedia.org/wiki/Google_Panda

    Google Panda is a major change to Google's search results ranking algorithm that was first released in February 2011. The change aimed to lower the rank of "low-quality sites" or "thin sites", [ 1 ] in particular " content farms ", [ 2 ] and return higher-quality sites near the top of the search results.

  4. RankBrain - Wikipedia

    en.wikipedia.org/wiki/RankBrain

    RankBrain has allowed Google to speed up the algorithmic testing it does for keyword categories to attempt to choose the best content for any particular keyword search. This means that old methods of gaming the rankings with false signals are becoming less and less effective, and the highest quality content from a human perspective is being ...

  5. 2020 in Review: The Year for Google - AOL

    www.aol.com/2020-review-google-130032808.html

    For Google and its parent company Alphabet, 2020 was a year of ups and downs. The company reached a milestone market value in January but then experienced its first revenue decline ever during the ...

  6. TrustRank - Wikipedia

    en.wikipedia.org/wiki/TrustRank

    TrustRank is an algorithm that conducts link analysis to separate useful webpages from spam and helps search engine rank pages in SERPs (Search Engine Results Pages). It is semi-automated process which means that it needs some human assistance in order to function properly.

  7. Discounted cumulative gain - Wikipedia

    en.wikipedia.org/wiki/Discounted_cumulative_gain

    Discounted cumulative gain (DCG) is a measure of ranking quality in information retrieval. It is often normalized so that it is comparable across queries, giving Normalized DCG (nDCG or NDCG) . NDCG is often used to measure effectiveness of search engine algorithms and related applications.

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