Essays about: "Kollaborativ filtrering"
Showing result 1 - 5 of 8 essays containing the words Kollaborativ filtrering.
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1. Recommender Systems Using Limited Dataset Sizes
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In order to create personalized recommendations for users on services such as e-commerce websites and streaming platforms, recommender systems often utilize various machine learning techniques. A common technique used in recommender systems is collaborative filtering which creates rating predictions based on similar users’ interests. READ MORE
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2. Recommending digital books to children : Acomparative study of different state-of-the-art recommendation system techniques
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Collaborative filtering is a popular technique to use behavior data in the form of user’s interactions with, or ratings of, items in a system to provide personalized recommendations of items to the user. This study compares three different state-of-the-art Recommendation System models that implement this technique, Matrix Factorization, Multi-layer Perceptron and Neural Matrix Factorization, using behavior data from a digital book platform for children. READ MORE
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3. Predicting future purchases with matrix factorization
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis aims to establish the efficacy of using matrix factorization to predict future purchases. Matrix factorisation is a machine learning method, commonly used to implement the collaborative filtering recommendation system. READ MORE
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4. Recommender system for IT security scanning service : Collaborative filtering in an error report scenario
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Recommender systems have become an integral part of the user interface of many web applications. Recommending items to buy, media to view or similar “next choice”-recommendations has proven to be a powerful tool to improve costumer experience and engagement. READ MORE
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5. New Methodologies for Fashion Recommender Systems
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Traditional Recommender Systems rely on finding similarities between users and/or between items. In its broadest definition, a Recommender System tries to predict the preference a user would give to an item. READ MORE
