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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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Koper ook geschreven Jansen, Melle (author)
A recommendation algorithm aims to predict the quality of a user's future interaction with certain items based on their previous interactions. As research progresses, these algorithms are becoming increasingly more complicated with the use of machine learning and neural networks. This paper looks into a more simple solution. The recommendation...
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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Musto, Cataldo (author), Tintarev, N. (author), Inel, O. (author), Polignano, Marco (author), Semeraro, Giovanni (author), Ziegler, Jürgen (author)
Adaptive and personalized systems have become pervasive technologies that are gradually playing an increasingly important role in our daily lives. Indeed, we are now used to interact every day with algorithms that help us in several scenarios, ranging from services that suggest us music to be listened to or movies to be watched, to personal...
conference paper 2021
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Beyhan, Yessin (author), Pera, M.S. (author)
The aim of this work is to explore common traits preferred across different age groups of children to identify the appeal of book covers. By analyzing visual attributes, visible objects, and implied stories inferred from the covers, we can gain insights into the elements that are most attractive to children up to 18 years old. These findings...
conference paper 2023
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Tintarev, N. (author), Rostami, Shahin (author), Smyth, Barry (author)
In this paper we consider how to help users to better understand their consumption profiles by examining two approaches to visualising user profiles - chord diagrams, and bar charts - aimed at revealing to users those regions of the recommendation space that are unknown to them, i.e. blind-spots. Both visualisations do this by connecting profile...
conference paper 2018
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Lu, Feng (author), Tintarev, N. (author)
Diversity-based recommender systems aim to select a wide rangeof relevant content for users, but diversity needs for users withdifferent personalities are rarely studied. Similarly, research onpersonality-based recommender systems has primarily focused onthe ‘cold-start problem’; few previous works have investigated howpersonality influences...
conference paper 2018
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Strucks, Christopher (author), Slokom, M. (author), Larson, M.A. (author)
Past research has demonstrated that removing implicit gender information from the user-item matrix does not result in substantial performance losses. Such results point towards promising solutions for protecting users’ privacy without compromising prediction performance, which are of particular interest in multistakeholder environments. Here,...
conference paper 2019
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Harte, Jesse (author), Zorgdrager, Wouter (author), Louridas, Panos (author), Katsifodimos, A (author), Jannach, Dietmar (author), Fragkoulis, M. (author)
Sequential recommendation problems have received increasing attention in research during the past few years, leading to the inception of a large variety of algorithmic approaches. In this work, we explore how large language models (LLMs), which are nowadays introducing disruptive effects in many AI-based applications, can be used to build or...
conference paper 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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Kim, Jaehun (author)
Machine learning (ML) has become a core technology for many real-world applications. Modern ML models are applied to unprecedentedly complex and difficult challenges, including very large and subjective problems. For instance, applications towards multimedia understanding have been advanced substantially. Here, it is already prevalent that...
doctoral thesis 2021
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Yang, J. (author)
Crowd knowledge creation plays a central role in many types of Web based information systems, ranging from community question-answering (CQA) systems (e.g. StackOverflow and Quora) to micro-task crowdsourcing systems (e.g. Amazon mTurk and CrowdFlower). In these systems, knowledge demands are generally fulfilled by means of tasks (e.g. questions...
doctoral thesis 2017
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Loni, B. (author)
Recommender Systems have become a crucial tool to serve personalized content and to promote online products and media, but also to recommend restaurants, events, news and dating profiles. The underlying algorithms have a significant impact on the quality of recommendations and have been the subject of many studies in the last two decades. In...
doctoral thesis 2018
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Li, Roger Zhe (author)
doctoral thesis 2023
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Psyllidis, A. (author), Yang, J. (author), Bozzon, A. (author)
Traditional methods for studying the activity dynamics of people and their social interactions in cities require time-consuming and resource-intensive observations and surveys. Dynamic online trails from geosocial networks (e.g. Twitter, Instagram, Flickr etc.) have been increasingly used as proxies for human activity, focusing on mobility...
journal article 2018
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Lu, Feng (author)
Current research on personality and diversity based Recommender Systems (RecSys) are mostly separated. In most diversity-based Recommender Systems, researchers usually endeavored to achieve an optimal balance between accuracy and diversity while they commonly set a same diversity level for all users. Different diversity needs for users with...
master thesis 2018
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Jiang, Xuehan (author)
Information systems, such as information retrieval machines and recommendation systems, utilize various user information and history behaviors to provide personalized content to users. However, a debate on whether the personalization in information systems can trigger the online echo chamber effect has emerged. The online echo chamber effect...
master thesis 2018
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Mulder, Mats (author)
Previous research on diversity in recommender systems define diversity as the opposite of similarity and propose methods that are based on topic diversity. Diversity in news media, however, is understood as multiperspectivity and scholars generally agree that fostering diversity is the key responsibility of the press in a democratic society....
master thesis 2020
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Lodha, Sneha (author)
<br/>One of the contributing factors to climate change is the release of gases, particularly carbon dioxide (CO2), which is amplified by the expanding E-commerce industry. E-commerce enterprises heavily depend on recommender systems as a means to incentivize consumers towards making product purchases. This master's thesis investigates the...
master thesis 2023
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