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  2. 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.

  3. Cold start (recommender systems) - Wikipedia

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

    In both cases, the cold start problem would imply that the user has to dedicate an amount of effort using the system in its 'dumb' state – contributing to the construction of their user profile – before the system can start providing any intelligent recommendations. [17] For example MovieLens, a web-based recommender system for movies, asks ...

  4. Matrix factorization (recommender systems) - Wikipedia

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

    This is an example of a cold-start problem, that is the recommender cannot deal efficiently with new users or items and specific strategies should be put in place to handle this disadvantage. [ 12 ] A possible way to address this cold start problem is to modify SVD++ in order for it to become a model-based algorithm, therefore allowing to ...

  5. Item-item collaborative filtering - Wikipedia

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

    As in user-user systems, similarity functions can use normalized ratings (correcting, for instance, for each user's average rating). 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 ...

  6. Slope One - Wikipedia

    en.wikipedia.org/wiki/Slope_One

    Examples of binary item-based collaborative filtering include Amazon's item-to-item patented algorithm [12] which computes the cosine between binary vectors representing the purchases in a user-item matrix. Being arguably simpler than even Slope One, the Item-to-Item algorithm offers an interesting point of reference. Consider an example.

  7. Pinterest (PINS) Q4 2024 Earnings Call Transcript - AOL

    www.aol.com/pinterest-pins-q4-2024-earnings...

    These associations between pins, searches, boards, products, and users make up our Taste Graph, which is the foundation of our AI recommendation engines and is used to amplify the quality of our ...

  8. List of performance analysis tools - Wikipedia

    en.wikipedia.org/wiki/List_of_performance...

    Arm MAP, a performance profiler supporting Linux platforms.; AppDynamics, an application performance management solution [buzzword] for C/C++ applications via SDK.; AQtime Pro, a performance profiler and memory allocation debugger that can be integrated into Microsoft Visual Studio, and Embarcadero RAD Studio, or can run as a stand-alone application.

  9. Roblox (RBLX) Q4 2024 Earnings Call Transcript - AOL

    www.aol.com/finance/roblox-rblx-q4-2024-earnings...

    Once again high growth rates across really all of our key financial and operating metrics and surpassing our guidance in every single data point where we provided guidance in our Q3 earnings call.