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  2. Slope One - Wikipedia

    en.wikipedia.org/wiki/Slope_One

    Slope One is a family of algorithms used for collaborative filtering, introduced in a 2005 paper by Daniel Lemire and Anna Maclachlan. [1] Arguably, it is the simplest form of non-trivial item-based collaborative filtering based on ratings. Their simplicity makes it especially easy to implement them efficiently while their accuracy is often on ...

  3. Recommender system - Wikipedia

    en.wikipedia.org/wiki/Recommender_system

    A recommender system (RecSys), or a recommendation system (sometimes replacing system with terms such as platform, engine, or algorithm), is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user.

  4. Item-item collaborative filtering - Wikipedia

    en.wikipedia.org/wiki/Item-item_collaborative...

    Second, the system executes a recommendation stage. It uses the most similar items to a user's already-rated items to generate a list of recommendations. Usually this calculation is a weighted sum or linear regression. This form of recommendation is analogous to "people who rate item X highly, like you, also tend to rate item Y highly, and you ...

  5. You influence recommendation algorithms just as much as ... - AOL

    www.aol.com/influence-recommendation-algorithms...

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  6. Collaborative filtering - Wikipedia

    en.wikipedia.org/wiki/Collaborative_filtering

    As the numbers of users and items grow, traditional CF algorithms will suffer serious scalability problems [citation needed]. 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 ...

  7. Matrix factorization (recommender systems) - Wikipedia

    en.wikipedia.org/wiki/Matrix_factorization...

    Matrix factorization algorithms work by decomposing the user-item interaction matrix into the product of two lower dimensionality rectangular matrices. [1] This family of methods became widely known during the Netflix prize challenge due to its effectiveness as reported by Simon Funk in his 2006 blog post, [ 2 ] where he shared his findings ...

  8. Cold start (recommender systems) - Wikipedia

    en.wikipedia.org/wiki/Cold_start_(recommender...

    The cold start problem is a well known and well researched problem for recommender systems.Recommender systems form a specific type of information filtering (IF) technique that attempts to present information items (e-commerce, films, music, books, news, images, web pages) that are likely of interest to the user.

  9. 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.