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  2. Collaborative filtering - Wikipedia

    en.wikipedia.org/wiki/Collaborative_filtering

    For example, with tens of millions of customers () and millions of items (), a CF algorithm with the complexity of is already too large. As well, many systems need to react immediately to online requirements and make recommendations for all users regardless of their millions of users, with most computations happening in very large memory machines.

  3. YouTube's algorithm more likely to recommend users ... - AOL

    www.aol.com/news/youtube-algorithm-more-likely...

    YouTube has a pattern of recommending right-leaning and Christian videos, even to users who haven’t previously interacted with that kind of content, according to a recent study of the platform ...

  4. Algorithmic radicalization - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_radicalization

    Algorithmic radicalization is the concept that recommender algorithms on popular social media sites such as YouTube and Facebook drive users toward progressively more extreme content over time, leading to them developing radicalized extremist political views. Algorithms record user interactions, from likes/dislikes to amount of time spent on ...

  5. Help:Wikitext - Wikipedia

    en.wikipedia.org/wiki/Help:Wikitext

    Most comments should go on the appropriate Talk page. The format is to surround the hidden text with "<!--" and "-->" and may cover several lines, e.g.: <!-- An example of hidden comments This won't be visible except in "edit" mode. --> Another way to include a comment in the wiki markup uses the {} template, which can be abbreviated as ...

  6. Commentz-Walter algorithm - Wikipedia

    en.wikipedia.org/wiki/Commentz-Walter_algorithm

    The paper on the algorithm was first published by Beate Commentz-Walter in 1979 through the Saarland University and typed by "R. Scherner". [1] The paper detailed two differing algorithms she claimed combined the idea of the Aho-Corasick and Boyer-Moore algorithms, which she called algorithms B and B1. The paper mostly focuses on algorithm B ...

  7. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Simplified example of training a neural network in object detection: The network is trained by multiple images that are known to depict starfish and sea urchins, which are correlated with "nodes" that represent visual features. The starfish match with a ringed texture and a star outline, whereas most sea urchins match with a striped texture and ...

  8. Search algorithm - Wikipedia

    en.wikipedia.org/wiki/Search_algorithm

    Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...

  9. Best-first search - Wikipedia

    en.wikipedia.org/wiki/Best-first_search

    Best-first search is a class of search algorithms which explores a graph by expanding the most promising node chosen according to a specified rule.. Judea Pearl described best-first search as estimating the promise of node n by a "heuristic evaluation function () which, in general, may depend on the description of n, the description of the goal, the information gathered by the search up to ...