Essays about: "Recommender Systems"
Showing result 1 - 5 of 136 essays containing the words Recommender Systems.
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1. Exploring the Future of Movie Recommendations : Increasing User Satisfaction using Generative Artificial Intelligence Conversational Agents
University essay from Umeå universitet/Institutionen för tillämpad fysik och elektronikAbstract : This thesis explores potential strategies to enhance user control and satisfaction within the movie selection process, with a particular focus on the utilization of conversational generative artificial intelligence, such as ChatGPT, for personalized movie recommendations. The study adopts a qualitative user-centered design thinking approach, aiming to compre-hensively understand user needs, goals, and behavior. READ MORE
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2. Context-Aware Fashion Recommender Systems to Provide Intent-based Recommendations to Customers
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : In recent years, Recommendation Systems have revolutionized how social media and ecommerce are used. Fashion Recommendation Systems have made it easier for customers to do shopping, by recommending items to them based on various factors, such as their previous orders, and their similarities to other users. READ MORE
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3. Designing Diverse Features to Reduce the Filter Bubble Effect on Social Media
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The filter bubble effect has been an active area of research that has been explored in various contexts within social media. Research on recommender system designs within filter bubbles has received a lot of attention, mainly due to its impact on the phenomena. READ MORE
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4. Integrating Machine Learning into Constraint Programming for Radio Recommendation in Radio Access Networks
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : This thesis introduces an approach for integrating Machine Learning into Constraint Programming for recommender systems. The main idea is to use clustering algorithms to divide the data into groups, which we use to derive objective functions that are used in a constraint solver. READ MORE
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5. Recommender Systems Using Limited Dataset Sizes
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In order to create personalized recommendations for users on services such as e-commerce websites and streaming platforms, recommender systems often utilize various machine learning techniques. A common technique used in recommender systems is collaborative filtering which creates rating predictions based on similar users’ interests. READ MORE