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Hittade 2 uppsatser som matchar ovanstående sökkriterier.

1. 1. Evaluating Cold-Start in Recommendation Systems Using a Hybrid Model Based on Factorization Machines and SBERT Embeddings

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

   Författare :Sabrina Chowdhury; [2022]
   Nyckelord :Natural Language Processing; Hybrid Recommender Systems; Cold-Start Problem; språkteknologi; hybrida rekommendationssystem; kallstartsproblemet;

   Sammanfattning : The item cold-start problem, which describes the difficulty of recommendation systems in recommending new items to users, remains a great challenge for recommendation systems that rely on past user-item interaction data. A popular technique in the current research surrounding the cold-start problem is the use of hybrid models that combine two or more recommendation strategies that may contribute with their individual advantages. LÄS MER

3. 2. A comparative study on the unsupervised classification of rat neurons by their morphology

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

   Författare :Sabrina Chowdhury; Added Kina; [2020]
   Nyckelord :;

   Sammanfattning : An ongoing problem regarding the automatic classification of neurons by their morphology is the lack of consensus between experts on neuron types. Unsupervised clustering using persistent homology as a descriptor for the morphology of neurons helps tackle the problem of bias in feature selection and has the potential of aiding neuroscience research in developing a framework for automatic neuron classification. LÄS MER