Searched for: subject%3A%22recommendation%22
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Sav, Andra Georgiana (author), Demetriou, A.M. (author), Liem, C.C.S. (author)
Machine Learning (ML) models influence all aspects of our lives. They also commonly are integrated in recommender systems, which facilitate users’ decision-making processes in various scenarios, such as e-commerce, social media, news and online learning. Training performed on large volumes of data is what ultimately drives such systems to...
journal article 2023
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Pathak, Royal (author), Spezzano, Francesca (author), Pera, M.S. (author)
Social networks are a platform for individuals and organizations to connect with each other and inform, advertise, spread ideas, and ultimately influence opinions. These platforms have been known to propel misinformation. We argue that this could be compounded by the recommender algorithms that these platforms use to suggest items potentially...
journal article 2023
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Garrido, Ángel Luis (author), Pera, M.S. (author), Bobed, Carlos (author)
Recommender Systems support a broad range of domains, each with peculiarities that recommendation algorithms must consider to produce appropriate suggestions. In the paper, we bring attention to a little-studied scenario related to the news domain: recommendations catering to media journalists. Based on the particular needs inherent to a...
journal article 2023
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Overgaard, Søren (author), Grupp, Thomas M. (author), Nelissen, R.G.H.H. (author), Cristofolini, Luca (author), Lübbeke, Anne (author), Jäger, Marcus (author), Fink, Matthias (author), Achakri, Hassan (author), Benazzo, Francesco (author), Günther, Klaus-Peter (author)
review 2023
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Tsigkari, D. (author), Iosifidis, G. (author), Spyropoulos, Thrasyvoulos (author)
Recommendations are employed by Content Providers (CPs) of streaming services in order to boost user engagement and their revenues. Recent works suggest that nudging recommendations towards cached items can reduce operational costs in the caching networks, e.g., Content Delivery Networks (CDNs) or edge cache providers in future wireless...
journal article 2023
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van Uffelen, N. (author), Taebi, B. (author), Pesch, U. (author)
Energy justice is often approached through the four tenets of procedural, distributive, restorative and recognition justice. Though these tenets are important placeholders for addressing what type of justice issues are involved, they require further normative substantiations. These are achieved by using principles of justice to specify why –...
journal article 2023
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Hulstijn, Joris (author), Tchappi, Igor (author), Najjar, Amro (author), Aydoğan, Reyhan (author)
Recommender systems aim to support their users by reducing information overload so that they can make better decisions. Recommender systems must be transparent, so users can form mental models about the system’s goals, internal state, and capabilities, that are in line with their actual design. Explanations and transparent behaviour of the...
conference paper 2023
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Ciatto, Giovanni (author), Magnini, Matteo (author), Buzcu, Berk (author), Aydoğan, Reyhan (author), Omicini, Andrea (author)
Building on prior works on explanation negotiation protocols, this paper proposes a general-purpose protocol for multi-agent systems where recommender agents may need to provide explanations for their recommendations. The protocol specifies the roles and responsibilities of the explainee and the explainer agent and the types of information...
conference paper 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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Sarkar, Priya (author)
Mathematical fairness notions introduced in literature aim to make algorithmic decisions fair. However, their usage has been criticized in domains such as recidivism and lending for producing unfair decisions. Questions regarding fairness, which also have an important role in hiring are giving way to concerns about the increasing adoption of...
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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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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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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