Sökning: "Singular value Filtering"

Visar resultat 1 - 5 av 10 uppsatser innehållade orden Singular value Filtering.

1. 1. Recommender Systems Using Limited Dataset Sizes

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Carl Bentzer; Harry Thulin; [2023]
   Nyckelord :;

   Sammanfattning : 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. LÄS MER

3. 2. Ingredient-based Group Recommender for Recipes (IGR2)

   Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :John Lindblad; Jonas Meddeb; [2022-02-16]
   Nyckelord :recommender systems; data science; user-generated content; contentbased filtering; singular value decomposition; recipes; food; group recommender systems;

   Sammanfattning : The number of food recipe options in modern society is vast and growing. While often being considered positive, the abundant options also lead to the so-called paradox of choice, i.e. that more options can lead to less happiness. LÄS MER

4. 3. Recommender System for Gym Customers

   Master-uppsats, Linköpings universitet/Statistik och maskininlärning

   Författare :Roshni Sundaramurthy; [2020]
   Nyckelord :Recommender system; collaborative filtering; matrix factorization; sparse matrix; latent semantic analysis; singular value decomposition; alternating least square; Bayesian personalized ranking; logistic matrix factorization; stochastic gradient descent; AUC metric; mean average precision; normalized discounted cumulative gain; Rekommendationssystem;

   Sammanfattning : Recommender systems provide new opportunities for retrieving personalized information on the Internet. Due to the availability of big data, the fitness industries are now focusing on building an efficient recommender system for their end-users. This thesis investigates the possibilities of building an efficient recommender system for gym users. LÄS MER

5. 4. Candidate - job recommendation system : Building a prototype of a machine learning – based recommendation system for an online recruitment company

   Magister-uppsats, Linnéuniversitetet/Institutionen för datavetenskap (DV)

   Författare :Nedzad Hafizovic; [2019]
   Nyckelord :machine learning; recommendation systems; collaborative filtering; mode-based; matrix factorization; data analysis; python; supervised learning; recruitment platform; singular value decomposition; non-negative matrix factorization;

   Sammanfattning : Recommendation systems are gaining more popularity because of the complexity of problems that they provide a solution to. There are many applications of recommendation systems everywhere around us. Implementation of these systems differs and there are two approaches that are most distinguished. LÄS MER

7. 5. Comparison and Improvement Of Collaborative Filtering Algorithms

   Kandidat-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

   Författare :Victor Hansjons Vegeborn; Hakim Rahmani; [2017]
   Nyckelord :;

   Sammanfattning : Recommender Systems is a topic several computer scientists have researched. With today’s e-commerce and Internet access, companies try to maximize their profit by utilizing var- ious recommender algorithms. One methodology used in such systems is Collaborative Filtering. LÄS MER