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Serving deep learning (DL) models on relational data has become a critical requirement across diverse commercial and scientific domains, sparking growing interest recently. In this visionary paper, we embark on a comprehensive exploration…

World models are emerging as a transformative paradigm in artificial intelligence, enabling agents to construct internal representations of their environments for predictive reasoning, planning, and decision-making. By learning latent…

Cloud computing has recently emerged as a major trend in distributed computing. We proposed a platform for selecting and configuring automatically an appropriate cloud environment that meets a set of consumer and provider requirements. It…

Here we describe two approaches to improve group information management (GIM) and draw on the results of prior works to implement them in software prototypes. The first aids browsing and retrieving from large and unfamiliar collections like…

The increasing popularity of deep learning models has created new opportunities for developing AI-based recommender systems. Designing recommender systems using deep neural networks requires careful architecture design, and further…

Design patterns provide a systematic way to convey solutions to recurring modeling challenges. This paper introduces design patterns for hybrid modeling, an approach that combines modeling based on first principles with data-driven modeling…

In modern mobile applications, users frequently encounter various new contexts, necessitating on-device continual learning (CL) to ensure consistent model performance. While existing research predominantly focused on developing lightweight…

Today, several people and organizations rely on cloud platforms. The reliability of cloud platforms depends heavily on the performance of their internal programs (agents). To better prevent regressions in cloud platforms, the design of…

After decades of engineering development and infrastructural investment, Internet connections have become commodity product in many countries, and Internet scale "cloud computing" has started to compete with traditional software business…

In this work we present Ludwig, a flexible, extensible and easy to use toolbox which allows users to train deep learning models and use them for obtaining predictions without writing code. Ludwig implements a novel approach to deep learning…

Game development is a complex task involving multiple disciplines and technologies. Developers and researchers alike have suggested that AI-driven game design assistants may improve developer workflow. We present a recommender system for…

In this study, we present a novel clustering-based collaborative filtering (CF) method for recommender systems. Clustering-based CF methods can effectively deal with data sparsity and scalability problems. However, most of them are applied…

Data management tasks require access to metadata, which is increasingly tracked by databases called data catalogs. Current catalogs are too dependent on users' understanding of data, leading to difficulties in large organizations of users…

Design systems represent a user interaction design and development approach that is currently of avid interest in the industry. However, little research work has been done to synthesize knowledge related to design systems in order to inform…

Software development comprises complex tasks which are performed by humans. It involves problem solving, domain understanding and communication skills as well as knowledge of a broad variety of technologies, architectures, and solution…

Distributed collaborative software development tends to make artifacts and decisions inconsistent and uncertain. We try to solve this problem by providing an information repository to reflect the state of works precisely, by managing the…

With the rapid advancement of digitization and intelligence, enterprise big data processing platforms have become increasingly important in data management. However, traditional monolithic architectures, due to their high coupling, are…

Cross-domain recommendation (CDR) is an important method to improve recommender system performance, especially when observations in target domains are sparse. However, most existing cross-domain recommendations fail to fully utilize the…

The collaboration of the real world and the virtual world, known as Digital Twin, has become a trend with numerous successful use cases. However, there are challenges mentioned in the literature that must be addressed. One of the most…

This paper describes two tools that aim to support decision making during the migration of IT systems to the cloud. The first is a modeling tool that produces cost estimates of using public IaaS clouds. The tool enables IT architects to…