Sökning: "Content-Based Filtering"

Visar resultat 1 - 5 av 35 uppsatser innehållade orden Content-Based Filtering.

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. 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

4. 3. 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

5. 4. 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

7. 5. A graph database implementation of an event recommender system

   M1-uppsats,

   Författare :Alexander Olsson; [2022]
   Nyckelord :Event; Recommender system; Neo4j; Graph database;

   Sammanfattning : The internet is larger than ever and so is the amount of information on the internet.The average user on the internet has next to endless possibilities and choices whichcan cause information overload. Companies have therefore developed systems toguide their users to find the right product or object in the form of recommendersystems. LÄS MER