Sökning: "Content-based systems"

Visar resultat 1 - 5 av 45 uppsatser innehållade orden Content-based systems.

1. 1. 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

3. 2. Design an emotionally positive experience via sentiment classification for social media recommendation systems : A case study in TikTok

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

   Författare :Yawen Deng; [2023]
   Nyckelord :recommendation system; social application; sentiment classification; emotions; UX; rekommendationssystem; social tillämpning; känslolägesklassificering; känslor; UX;

   Sammanfattning : Recommendation system benefits social media by attracting users with the posts they prefer. The recommended posts, however, may not align with what users really need to browse, especially in terms of emotion. LÄS MER

4. 3. Overcoming The New Item Problem In Recommender Systems : A Method For Predicting User Preferences Of New Items

   Master-uppsats, Stockholms universitet/Statistiska institutionen

   Författare :Alice Jonason; [2023]
   Nyckelord :Recommender systems; Content-based systems; Implicit ratings; Latent Dirichlet Allocation; Vector Space Model;

   Sammanfattning : This thesis addresses the new item problem in recommender systems, which pertains to the challenges of providing personalized recommendations for items which have limited user interaction history. The study proposes and evaluates a method for generating personalized recommendations for movies, shows, and series on one of Sweden’s largest streaming platforms. 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