48 research outputs found
Machine learning-based dynamic frequency and bandwidth allocation in self-organized LTE dense small cell deployments
Towards a Taxonomy of Cognitive RPA Components
Robotic Process Automation (RPA) is a discipline that is
increasingly growing hand in hand with Artificial Intelligence (AI) and
Machine Learning enabling the so-called cognitive automation. In such
context, the existing RPA platforms that include AI-based solutions clas sify their components, i.e. constituting part of a robot that performs a
set of actions, in a way that seems to obey market or business deci sions instead of common-sense rules. To be more precise, components
that present similar functionality are identified with different names and
grouped in different ways depending on the platform that provides the
components. Therefore, the analysis of different cognitive RPA platforms
to check their suitability for facing a specific need is typically a time consuming and error-prone task. To overcome this problem and to pro vide users with support in the development of an RPA project, this
paper proposes a method for the systematic construction of a taxonomy
of cognitive RPA components. Moreover, such a method is applied over
components that solve selected real-world use cases from the industry
obtaining promising resultsMinisterio de Economía y Competitividad TIN2016-76956-C3-2-RJunta de Andalucía CEI-12-TIC021Centro para el Desarrollo Tecnológico Industrial P011-19/E0