Essays about: "Streaming Recommender Systems"
Showing result 6 - 10 of 16 essays containing the words Streaming Recommender Systems.
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6. Recommender system for IT security scanning service : Collaborative filtering in an error report scenario
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : 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. READ MORE
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7. Improving Recommender Engines for Video Streaming Platforms with RNNs and Multivariate Data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : 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. READ MORE
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8. Finding time-based listening habits in users music listening history to lower entropy in data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In a world where information, entertainment and e-commerce are growing rapidly in terms of volume and options, it can be challenging for individuals to find what they want. Search engines and recommendation systems have emerged as solutions, guiding the users. READ MORE
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9. Contextualizing music recommendations : A collaborative filtering approach using matrix factorization and implicit ratings
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : Recommender systems are helpful tools employed abundantly in online applications to help users find what they want. This thesis re-purposes a collaborative filtering recommender built for incorporating social media (hash)tags to be used as a context-aware recommender, using time of day and activity as contextual factors. READ MORE
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10. StreamER: Evaluation Framework For Streaming Recommender Systems
University essay from Malmö universitet/Fakulteten för teknik och samhälle (TS)Abstract : Recommender systems have gained a lot of popularity in recent times dueto their application in the wide range of fields. Recommender systems areintended to support users in finding the relevant items based on their interestsand preferences. READ MORE