Sökning: "Rekommendationssystem"

Visar resultat 16 - 20 av 106 uppsatser innehållade ordet Rekommendationssystem.

  1. 16. GROCERY PRODUCT RECOMMENDATIONS : USING RANDOM INDEXING AND COLLABORATIVE FILTERING

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

    Författare :Axel Orrenius; Axel Wiebe Werner; [2022]
    Nyckelord :Alternating Least Squares; Collaborative Filtering; Machine Learning; Random Indexing; Rapid-Delivery; Product Recommendations;

    Sammanfattning : The field of personalized product recommendation systems has seen tremendous growth in recent years. The usefulness of the algorithms’ abilities to filter out data from vast sets has been shown to be crucial in today’s information-heavy online experience. LÄS MER

  3. 17. Attention-based Multi-Behavior Sequential Network for E-commerce Recommendation

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

    Författare :Zilong Li; [2022]
    Nyckelord :Recommendation System; Sequential Recommendation; Click-through Rate Model; Transformer; Multi-Task Learning; Sistema di Raccomandazione; Raccomandazione Sequenziale; Modello di Percentuale di Clic; Trasformatore; Apprendimento Multitasking; Rekommendationssystem; Sekventiell rekommendation; Klickfrekvensmodell; Transformator; Multi-Task Learning;

    Sammanfattning : The original intention of the recommender system is to solve the problem of information explosion, hoping to help users find the content they need more efficiently. In an e-commerce platform, users typically interact with items that they are interested in or need in a variety of ways. For example, buying, browsing details, etc. LÄS MER

  4. 18. Recommender system for IT security scanning service : Collaborative filtering in an error report scenario

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

    Författare :Jonas Thunberg; [2022]
    Nyckelord :Collaborative Filtering; Vulnerability Scanning; IT-Security; Recommender System;

    Sammanfattning : Recommender systems have become an integral part of the user interface of many web applications. Recommending items to buy, media to view or similar “next choice”-recommendations has proven to be a powerful tool to improve costumer experience and engagement. LÄS MER

  5. 19. Improving Recommender Engines for Video Streaming Platforms with RNNs and Multivariate Data

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

    Författare :Daniel Pérez Felipe; [2022]
    Nyckelord :Recurrent neural networks; Recommender systems; Video on demand; Clustering methods; Återkommande neurala nätverk; Rekommendationssystem; Video på begäran; Klustermetoder; Redes neuronales recurrentes; Sistemas de recomendación; Vídeo bajo demanda; Métodos de clustering;

    Sammanfattning : For over 4 years now, there has been a fierce fight for staying ahead in the so-called ”Streaming War”. The Covid-19 pandemic and its consequent confinement only worsened the situation. In such a market where the user is faced with too many streaming video services to choose from, retaining customers becomes a necessary must. LÄS MER

  7. 20. Extremism på digitala plattformar : En kvalitativ studie av TikToks rekommendationsalgoritm

    Kandidat-uppsats, Högskolan i Halmstad/Akademin för informationsteknologi

    Författare :Johanna Kahlqvist; Ebba Falk; [2022]
    Nyckelord :;

    Sammanfattning : The threat of violent extremism is considered by authorities as one of the largest today. Political extremism has increased over the years and the number of politically motivated terrorist incidents in the Western world is higher than religiously motivated. LÄS MER