Related papers: Catalog of Formalized Application Integration Patt…
Explainable AI (XAI) is slowly becoming a key component for many AI applications. Rule-based and modified backpropagation XAI approaches however often face challenges when being applied to modern model architectures including innovative…
AARC (Authentication and Authorisation for Research Communities) is a two-year EC-funded project to develop and pilot an integrated cross-discipline authentication and authorisation framework, building on existing authentication and…
This paper presents an overview of S2AEA (v2) (Strategic Alignment Assessment based on Enterprise Architecture (version2)), a platform for modelling enterprise architecture and for assessing strategic alignment based on internal enterprise…
Most modern formalisms used in Databases and Artificial Intelligence for describing an application domain are based on the notions of class (or concept) and relationship among classes. One interesting feature of such formalisms is the…
Web-based application developers face a dizzying array of platforms, languages, frameworks and technical artifacts to choose from. We survey, classify, and compare technologies supporting Web application development. The classification is…
Explainable artificial intelligence is an emerging and evolving concept. Its impact on construction, though yet to be realised, will be profound in the foreseeable future. Still, XAI has received limited attention in construction. As a…
Digitalization efforts often face a key challenge: business processes must not only be efficient in achieving their goals but also adhere to legal regulations. Business process compliance refers to aligning processes with these regulations.…
Nowadays, developers often reuse existing APIs to implement their programming tasks. A lot of API usage patterns are mined to help developers learn API usage rules. However, there are still many missing variables to be synthesized when…
Modern database systems face a significant challenge in effectively handling the Variety of data. The primary objective of this paper is to establish a unified data model and theoretical framework for multi-model data management. To achieve…
Web conferencing tools have entered the mainstream of business applications. Using web conferencing for IEEE conferences has a good potential of adding value to both organizers and participants. Authors propose a concept of Truly Integrated…
Software systems are increasingly relying on Artificial Intelligence (AI) and Machine Learning (ML) components. The emerging popularity of AI techniques in various application domains attracts malicious actors and adversaries. Therefore,…
Large language models (LLMs) have gained significant interest in industry due to their impressive capabilities across a wide range of tasks. However, the widespread adoption of LLMs presents several challenges, such as integration into…
The unification of statistical (data-driven) and symbolic (knowledge-driven) methods is widely recognised as one of the key challenges of modern AI. Recent years have seen large number of publications on such hybrid neuro-symbolic AI…
Entity resolution (record linkage, microclustering) systems are notoriously difficult to evaluate. Looking for a needle in a haystack, traditional evaluation methods use sophisticated, application-specific sampling schemes to find matching…
Enterprise information systems can be developed following a model-driven paradigm. This way, models that represent the organisational work practice are used to produce models that represent the information system. Current software…
Use case driven development methodologies put use cases at the center of the software development process. However, in order to support automated development and analysis, use cases need to be appropriately formalized. This will also help…
Context: The complexity of modern safety-critical systems in industries keep on increasing due to the rising number of features and functionalities. This calls for formal methods in order to entrust confidence in such systems. Nevertheless,…
Data-driven approaches are becoming more common as problem-solving techniques in many areas of research and industry. In most cases, machine learning models are the key component of these solutions, but a solution involves multiple such…
Big Data technology is described. Big data is a popular term used to describe the exponential growth and availability of data, both structured and unstructured. There is constructed dataspace architecture. Dataspace has focused solely - and…
In resolving instances of a computational problem, if multiple instances of interest share a feature in common, it may be fruitful to compile this feature into a format that allows for more efficient resolution, even if the compilation is…