Sökning: "Content based filtering"

Visar resultat 1 - 5 av 58 uppsatser innehållade orden Content based filtering.

  1. 1. Andra lyssnar även på... : En kvalitativ studie om användarupplevelsen av Spotifys rekommendationssystem.

    Kandidat-uppsats, Umeå universitet/Institutionen för informatik

    Författare :Camilla Fabricio de Barros; Julia Kinnvall; Willmer Pousette Lilja; [2023]
    Nyckelord :Rekommendationssystem; Spotify; användarupplevelse;

    Sammanfattning : The overload of content in digital services demands a way to filter the content for each individual user. The solution to this problem has come to be recommendation systems, which creates recommendations after the behavior patterns and preferences of each user. LÄS MER

  3. 2. Context-Aware Fashion Recommender Systems to Provide Intent-based Recommendations to Customers

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Edda Waciira; Marah Thomas; [2023]
    Nyckelord :e-commerce; Fashion Recommendation Systems; Machine Learning; Recommendation Systems;

    Sammanfattning : In recent years, Recommendation Systems have revolutionized how social media and ecommerce are used. Fashion Recommendation Systems have made it easier for customers to do shopping, by recommending items to them based on various factors, such as their previous orders, and their similarities to other users. LÄS MER

  4. 3. Constructing and representing a knowledge graph(KG) for Positive Energy Districts (PEDs)

    Master-uppsats, Högskolan Dalarna/Institutionen för information och teknik

    Författare :Mahtab Davari; [2023]
    Nyckelord :Knowledge graph; Positive Energy Districts PEDs ; longest path; Questions and Answers; Community Detection; Node Embedding; t-SNE plots; Edge Prediction;

    Sammanfattning : In recent years, knowledge graphs(KGs) have become essential tools for visualizing concepts and retrieving contextual information. However, constructing KGs for new and specialized domains like Positive Energy Districts (PEDs) presents unique challenges, particularly when dealing with unstructured texts and ambiguous concepts from academic articles. LÄS MER

  5. 4. Help Document Recommendation System

    Master-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)

    Författare :Keerthi Vijay Kumar; Pinky Mary Stanly; [2023]
    Nyckelord :Document similarity; Recommender systems; content-based filtering; collaborative filtering; Term Frequency-Inverse Document Frequency TF-IDF ; Bidirectional Encoder Representation from Transformers BERT ; Non-Negative Matrix Factorisation NMF ; cosine similarity; K-means clustering;

    Sammanfattning : Help documents are important in an organization to use the technology applications licensed from a vendor. Customers and internal employees frequently use and interact with the help documents section to use the applications and know about the new features and developments in them. LÄS MER

  7. 5. Developing Machine Learning-based Recommender System on Movie Genres Using KNN

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Anthony Ezeh; [2023]
    Nyckelord :: Movie Recommender System; Machine Learning; Content-based Filtering; Collaborative Filtering; KNN Algorithms; Classification Algorithm;

    Sammanfattning : With an overwhelming number of movies available globally, it can be a daunting task for users to find movies that cater to their individual preferences. The vast selection can often leave people feeling overwhelmed, making it challenging to pick a suitable movie. LÄS MER