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By the growing trend of online shopping and e-commerce websites, recommendation systems have gained more importance in recent years in order to increase the sales ratios of companies. Different algorithms on recommendation systems are used…
Refactoring is widely recognized as one of the efficient techniques to manage technical debt and maintain a healthy software project through enforcing best design practices or coping with design defects. Previous refactoring surveys have…
Improved software discovery is a prerequisite for greater software reuse: after all, if someone cannot find software for a particular task, they cannot reuse it. Understanding people's approaches and preferences when they look for software…
Refactoring is a maintenance activity that aims to improve design quality while preserving the behavior of a system. Several (semi)automated approaches have been proposed to support developers in this maintenance activity, based on the…
Reinforcement learning serves as a potent tool for modeling dynamic user interests within recommender systems, garnering increasing research attention of late. However, a significant drawback persists: its poor data efficiency, stemming…
Modern recommender systems operate in uniquely dynamic settings: user interests, item pools, and popularity trends shift continuously, and models must adapt in real time without forgetting past preferences. While existing tutorials on…
The introduction of new tools in people's workflow has always been promotive of new creative paths. This paper discusses the impact of using computational tools in the performance of creative tasks, especially focusing on graphic design.…
Open Source Software (OSS) is forming the spines of technology infrastructures, attracting millions of talents to contribute. Notably, it is challenging and critical to consider both the developers' interests and the semantic features of…
Current practice for evaluating recommender systems typically focuses on point estimates of user-oriented effectiveness metrics or business metrics, sometimes combined with additional metrics for considerations such as diversity and…
Software remodularization through clustering is a common practice to improve internal software quality. However, the true benefit of software clustering is only realized if developers follow through with the recommended refactoring…
Over the last decades has emerged a rich literature on the evaluation of recommendation systems. However, less is written about how to efficiently combine different evaluation methods from this rich field into a single efficient evaluation…
So far there have been several efforts for developing software process simulators. However, the approaches for developing the simulators seem to have been ad-hoc and no systematic methodology exists. Since modeling and simulation in support…
This paper identifies the factors that have an impact on mobile recommender systems. Recommender systems have become a technology that has been widely used by various online applications in situations where there is an information overload…
In this paper, we study shortlists as an interface component for recommender systems with the dual goal of supporting the user's decision process, as well as improving implicit feedback elicitation for increased recommendation quality. A…
All software development processes include steps where several alternatives induce a choice, a decision-making. Sometimes, methodologies offer a way to make decisions. However, in a lot of cases, the arguments to carry out the decision are…
Ranking is a core task in recommender systems, which aims at providing an ordered list of items to users. Typically, a ranking function is learned from the labeled dataset to optimize the global performance, which produces a ranking score…
The most important way to achieve higher performance in computer systems is through heterogeneous computing, i.e., by adopting hardware platforms containing more than one type of processor, such as CPUs, GPUs, and FPGAs. Several types of…
Educational recommender systems have become a necessity in the recent years due to overload of available educational resource which makes it difficult for an individual to manually hunt for the required resource on the internet. E-learning…
Recommender systems are expected to be assistants that help human users find relevant information automatically without explicit queries. As recommender systems evolve, increasingly sophisticated learning techniques are applied and have…
We detail some lessons learned while designing and testing a decision-theoretic advising support tool for undergraduates at a large state university. Between 2009 and 2011 we conducted two surveys of over 500 students in multiple majors and…