Searched for: subject%3A%22recommender%255C%2Bsystem%22
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Bruyn, Tim (author)
This research is a case study investigating the effect of participation in the development process of a network-based scientist-journalist recommender system on the mental model of digital innovation of a team of communication professionals from Delft University of Technology and Naturalis Biodiversity Center.<br/> <br/>Communication...
master thesis 2023
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Qiu, Ziang (author)
Recently, a few children-centered recommendation systems have been created and evaluated. How- ever, these systems required user interaction to cre- ate ground truth to evaluate the result. This research aims to compare some of the traditional recommen- dation models and explore which trait could impact the recommendation process most for...
bachelor thesis 2023
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Swart, Stijn (author)
Recommender systems are a useful tool for match- ing readers with books. However, the lack of user data from children, both due to privacy concerns as well as a low incentive to leave reviews, results in existing systems proving inadequate at recom- mending to the youth. It has been shown that chil- dren have a different relation regarding...
bachelor thesis 2023
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Alkhiami, Mohamad awab (author)
This study examines traits that may be derived from book metadata and identifies statistically signifi- cant patterns and trends in order to assist recom- mender system designers for children’s books in selecting the most important traits to take into ac- count. This research focuses on descriptive such as publish year and structural metadata...
bachelor thesis 2023
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van Smaalen, Mees (author)
Reading is an essential skill for any child to learn, and finding enjoyment in it can greatly contribute to developing proper reading comprehension. Finding the books they like could prove to be difficult. Utilizing collaborative filtering recommender systems to recommend books to children is a tricky task, the lack of user feedback makes it...
bachelor thesis 2023
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Beyhan, Yessin (author)
The cover of a children's book could play a crucial role in attracting the attention of young readers and influencing their decision to pick up and read the book. In this study, we aim to identify the factors that contribute to the appeal of children's book covers. Given that the target audience for children's books changes as children grow...
bachelor thesis 2023
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Izadi, M. (author), Nejati, Mahtab (author), Heydarnoori, Abbas (author)
Software-related platforms such as GitHub and Stack Overflow, have enabled their users to collaboratively label software entities with a form of metadata called topics. Tagging software repositories with relevant topics can be exploited for facilitating various downstream tasks. For instance, a correct and complete set of topics assigned to a...
journal article 2023
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Magnini, Matteo (author), Ciatto, Giovanni (author), Cantürk, Furkan (author), Aydoğan, Reyhan (author), Omicini, Andrea (author)
Background and objective:This paper focuses on nutritional recommendation systems (RS), i.e. AI-powered automatic systems providing users with suggestions about what to eat to pursue their weight/body shape goals. A trade-off among (potentially) conflictual requirements must be taken into account when designing these kinds of systems, there...
journal article 2023
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Maddila, C.S. (author)
The software development life cycle (SDLC) for a developer has increased in complexity and scale. With the advent of DevOps processes, the gap between development and operations teams reduced significantly. Developers are now expected to perform different roles from coding to operational support in the new model of software development. This...
doctoral thesis 2022
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Chandrashekar, Rohan (author)
Humans make decisions when presented with choices based on influences. The Internet today presents people with abundant choices to choose from. Recommending choices with an emphasis on people's preferences has become increasingly sought. Grundy (1979), the first computer librarian Recommender System (RS), provided users with book recommendations...
master thesis 2022
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de With, Wim (author)
Recommender systems usually base their predictions on user-item interaction, a technique known as collaborative filtering. Vendors that utilize collaborative filtering generally exclusively use their own user-item interactions, but the accuracy of the recommendations may improve if several vendors share their data. Since user-item interaction...
master thesis 2022
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Jongerius, Ricardo (author)
Online dating has become the most popular method of finding potential romantic partners. At the core of these platforms, there is a reciprocal recommender system which recommends users to other users on the platform. Breeze is an example of such a dating app, serving its users potential romantic partners every day in the hopes of sending them on...
master thesis 2022
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Kalisvaart, Raoul (author)
We all know the possible consequences of global warming, rising temperatures, flooded cities and destroyed ecosystems. One of the causes is the emission of gases, predominantly CO2, which is increased by the growing E-commerce market. E-commerce companies rely on recommender systems to stimulate users to purchase products. We are convinced that...
master thesis 2022
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Jung, Ji Youn (author)
Research has shown how people anthropomorphize conversational agents (CA) and unconsciously bring their gender stereotypes into human-agent interaction. For this reason, there has been a long lasted dilemma on whether designers should design CAs that conform to or violate stereotypical expectations. Despite the urgency and importance of...
master thesis 2022
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Karahan, Asli (author)
Healthcare recommender systems emerged to help patients make better decisions for their health, leveraging the vast amount of data and patient experience. One type of this system focuses on recommending the most appropriate physician based on previous patient feedback in the form of ratings. Such advice can be challenging to generate for new...
master thesis 2022
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Crul, Thomas (author)
Even though the abaility to recommend items in the long tail is one of the main strengths of recommendation systems, modern models still show decreased performance when recommending these niche items. Various bipartite and tripartite graph-based models have been proposed that are specifically tailored to solving this long tail issue. This study...
bachelor thesis 2022
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Mundhra, Yash (author)
Recommender systems are an essential part of online businesses in today's day and age. They provide users with meaningful recommendations for items and products. A frequently occurring problem in recommender systems is known as the long-tail problem. It refers to a situation in which a majority of the items in the data set have limited ratings...
bachelor thesis 2022
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Pantea, Luca (author)
Recommender Systems play a significant part in filtering and efficiently prioritizing relevant information to alleviate the information overload problem and maximize user engagement. Traditional recommender systems employ a static approach towards learning the user's preferences, relying on logged previous interactions with the system,...
bachelor thesis 2022
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Mariūnas, Karolis (author)
Recommender systems (RS) assist users in making decisions by filtering content that the user would likely find relevant. Standard techniques like collaborative filtering exploit user similarities to find the recommendations assuming that similar users are likely to be interested in the same items. On the other hand, graph RS borrow techniques...
bachelor thesis 2022
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Ionescu, Andrei (author)
Developers do not want to reinvent the wheel when developing software systems. Open-source software repositories are packed with resources that may assist developers with their work. Since Github enabled repository tagging, a new opportunity arose to help developers find the needed resources tailored to their needs. The current work proposes two...
bachelor thesis 2022
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