Visual Identification of Inconsistency in Pattern

The visual identification of inconsistencies in patterns is an area in computing that has been understudied. While pattern visualisation exposes the relationships among identified regularities, it is still very important to identify inconsistencies (irregularities) in identified patterns. The significance of identifying inconsistencies for example in the growth pattern of children of a particular age will enhance early intervention such as dietary modifications for stunted children. It is described in this chapter, the need to have a system that identifies inconsistencies in identified pattern of a dataset. Also, techniques that enable the visual identification of inconsistencies in patterns such as fault tolerance and colour coding are described. Two approaches are presented in this chapter for visualising inconsistencies in patterns namely; visualising inconsistencies in objects with many attribute values and visual comparison of an investigated dataset with a case control dataset. These approaches are associated with tools which were developed by the authors of this chapter: Firstly, ConTra which allows its users to mine and analyse the contradictions in attribute values whose data does not abide by the mutual exclusion rule of the dataset. Secondly, Datax which mines missing data; enables the visualisation of the missingness and the identification of the associated patterns. Finally, WellGrowth which explores Children’s growth dataset by comparing an investigated dataset (data obtained from a Primary Health Centre) with a case control dataset (data from the website of World Health Organisation). Instances of inconsistencies as discovered in the explored datasets are discussed

Periodismo robot : aplicaciones de la tecnología, los algoritmos y la automatización en la comunicación

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias de la Información, leída el 03-02-2023Esta disertación expone y analiza cómo la tecnología, el uso de algoritmos y la automatización de procesos — técnicas propias de disciplinas como la matemática, la estadística o la ingeniería informática — han transformado el sector del periodismo y el perfil del profesional de la información. Este estudio elabora una taxonomía y describe las diferentes disciplinas periodísticas que han surgido en la intersección entre periodismo y tecnología, así como sus características, evolución, beneficios y desafíos que suponen. Además, esta tesis investiga el impacto que la automatización, es decir, el periodismo robot, ha tenido en el periodismo, analizando el futuro de la comunicación bajo el paraguas del periodismo robot.This dissertation exposes and analyzes how technology, the use of algorithms and automation — techniques from disciplines such as Math, Statistics or Computer engineering— have transformed journalism and the role of the reporter. This study creates a taxonomy of the different disciplines that have emerged from the intersection between journalism and technology, describing their main characteristics, evolution over time, benefits and challenges journalists face today working in this field. In addition, this thesis investigates the impact that automation has had in journalism, analyzing the future of mass media under the umbrella of robot journalism.Fac. de Ciencias de la InformaciónTRUEunpu