Essays about: "Content-based Filter"

Showing result 1 - 5 of 8 essays containing the words Content-based Filter.

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

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

   Abstract : 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. READ MORE

3. 2. A graph database implementation of an event recommender system

   University essay from

   Author : Alexander Olsson; [2022]
   Keywords : Event; Recommender system; Neo4j; Graph database;

   Abstract : 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. READ MORE

4. 3. A Comparison between Different Recommender System Approaches for a Book and an Author Recommender System

   University essay from Linköpings universitet/Interaktiva och kognitiva system

   Author : Jesper Hedlund; Emma Nilsson Tengstrand; [2020]
   Keywords : Recommender System; Collaborative Filter; Matrix Factorization; Content-based Filter; Doc2Vec;

   Abstract : A recommender system is a popular tool used by companies to increase customer satisfaction and to increase revenue. Collaborative filtering and content-based filtering are the two most common approaches when implementing a recommender system, where the former provides recommendations based on user behaviour, and the latter uses the characteristics of the items that are recommended. READ MORE

5. 4. Switching hybrid recommender system to aid the knowledge seekers

   University essay from Uppsala universitet/Institutionen för informationsteknologi

   Author : Alexander Backlund; [2020]
   Keywords : ML; Machine Learning; Recommender System; Information Filtering; Content-Based Filtering; Collaborative Filtering; Hybrid Filtering; KNN; MF; Matrix Factorization;

   Abstract : In our daily life, time is of the essence. People do not have time to browse through hundreds of thousands of digital items every day to find the right item for them. This is where a recommendation system shines. Tigerhall is a company that distributes podcasts, ebooks and events to subscribers. READ MORE

6. 5. Implementing a Nudge to Prevent Email Phishing

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Viktor Vitek; Taqui Syed Shah; [2019]
   Keywords : Hacking; Phishing; Social Engineering; Psychology; Nudge; ; Dataintrång; Nätfiske; Social Manipulation; Psykologi; Nudge; ;

   Abstract : Phishing is a reoccurring issue, which uses social engineering as an attack strategy. The prevention of these attacks is often content-based filters. These solutions are however not always perfect, and phishing emails can still be able to get through the filters. We suggest a new strategy to combat phishing. READ MORE