Sökning: "Content-based filtering"

Visar resultat 21 - 25 av 35 uppsatser innehållade orden Content-based filtering.

  1. 21. Content based filtering for application software

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

    Författare :David Lindström; [2018]
    Nyckelord :Recommender system; content based filtering;

    Sammanfattning : In the study, two methods for recommending application software were implemented and evaluated based on their ability to recommend alternative applications with related functionality to the one that a user is currently browsing. One method was based on Term Frequency–Inverse Document Frequency (TF-IDF) and the other was based on Latent Semantic Indexing (LSI). LÄS MER

  3. 22. Effektiviteten av rekommendationssystems olika filtreringstekniker: En strukturerad litteraturstudie

    Kandidat-uppsats, Uppsala universitet/Informationssystem

    Författare :Fredrik Lundström; Sofia Sandberg; [2018]
    Nyckelord :Recommender systems; Recommendation systems; Electronic Commerce; E-Commerce; Literature review; Content based filtering; Collaborative filtering; Hybrid filtering; Rekommendationssystem; E-Handel; Rekommendations System; Litteraturstudie; Innehållsbaserad Filtreringsteknik; Kollaborativ Filtreringsteknik; Hybrid filtreringsteknik;

    Sammanfattning : Mängden data som transporteras över Internet idag är stor. Vilket innebär att det finns ett överflöd av information och ett behov för att urskilja relevant innehåll mot irrelevant. För att uppnå detta används rekommendationssystem som i sin tur använder olika filtreringstekniker. LÄS MER

  4. 23. Recommender Systems for Movie Recommendations

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

    Författare :Toni Hinas; Isabelle Ton; [2018]
    Nyckelord :;

    Sammanfattning : Recommender systems are becoming a large and important market, with commerce moving to the internet and the ability to keep a larger stock of products, one of the biggest hurdles is to organize and show the right product to the right customer. Recommender systems aim at tailoring their products based on their customer need, by predicting how much a user would like a particular product. LÄS MER

  5. 24. Fördelar med att applicera Collaborative Filtering på Steam : En utforskande studie

    Kandidat-uppsats,

    Författare :Martin Bergqvist; Jim Glansk; [2018]
    Nyckelord :;

    Sammanfattning : The use of recommender systems is everywhere. On popular platforms such as Netflix and Amazon, you are always given new recommendations on what to consume next, based on your specific profiling. This is done by cross-referencing users and products to find probable patterns. LÄS MER

  7. 25. Constant ratio optimization in dual-algorithm naive approach to recommendation systems

    Kandidat-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

    Författare :Gabriel Ingemarsson; Rickard Kodet; [2017]
    Nyckelord :;

    Sammanfattning : Recommendation systems, i.e. systems that based on some kind of input data produce recommendations for users, are key components of content discovery in today’s information-rich environment. LÄS MER