Computational Models (of Narrative) for Literary Studies

In the last decades a growing body of literature in Artificial Intelligence (AI) and Cognitive Science (CS) has approached the problem of narrative understanding by means of computational systems. Narrative, in fact, is an ubiquitous element in our everyday activity and the ability to generate and understand stories, and their structures, is a crucial cue of our intelligence. However, despite the fact that - from an historical standpoint - narrative (and narrative structures) have been an important topic of investigation in both these areas, a more comprehensive approach coupling them with narratology, digital humanities and literary studies was still lacking. With the aim of covering this empty space, in the last years, a multidisciplinary effort has been made in order to create an international meeting open to computer scientist, psychologists, digital humanists, linguists, narratologists etc.. This event has been named CMN (for Computational Models of Narrative) and was launched in the 2009 by the MIT scholars Mark A. Finlayson and Patrick H. Winston1

Toward a model of computational attention based on expressive behavior: applications to cultural heritage scenarios

Our project goals consisted in the development of attention-based analysis of human expressive behavior and the implementation of real-time algorithm in EyesWeb XMI in order to improve naturalness of human-computer interaction and context-based monitoring of human behavior. To this aim, perceptual-model that mimic human attentional processes was developed for expressivity analysis and modeled by entropy. Museum scenarios were selected as an ecological test-bed to elaborate three experiments that focus on visitor profiling and visitors flow regulation

Access to recorded interviews: A research agenda

Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed

Cognition-Based Evaluation of Visualisation Frameworks for Exploring Structured Cultural Heritage Data

It is often claimed that Information Visualisation (InfoVis) tools improve the audience’s engagement with the display of cultural heritage (CH) collections, open up CH content to new audiences and support teaching and learning through interactive experiences. But there is a lack of studies systematically evaluating these claims, particularly from the perspective of modern educational theory. As far as the author is aware no experimental investigation has been undertaken until now, that attempts to measure deeper levels of user engagement and learning with InfoVis tools. The investigation of this thesis complements InfoVis research by initiating a human-centric approach since little previous research has attempted to incorporate and integrate human cognition as one of the fundamental components of InfoVis. In this thesis, using Bloom’s taxonomy of learning objectives as well as individual learning characteristics (i.e. cognitive preferences), I have evaluated the visitor experience of an art collection both with and without InfoVis tools (between subjects design). Results indicate that whilst InfoVis tools have some positive effect on the lower levels of learning, they are less effective for higher levels. In addition, this thesis shows that InfoVis tools seem to be more effective when they match specific cognitive preferences. These results have implications for both the designers of tools and for CH venues in terms of expectation of effectiveness and exhibition design; the proposed cognitive based evaluation framework and the results of this investigation could provide a valuable baseline for assessing the effectiveness of visitors’ interaction with the artifacts of online and physical exhibitions where InfoVis tools such as Timelines and Maps along with storytelling techniques are being used

The effect of 3D realism and meaning making: A conceptual model

Field studies show that computer graphics, as in this case the 3D model of a heritage building, are only iconic representations rich perceived differently by individuals. Still, there is lack of evidence on how realistic 3D in contributes to the meaning making process.This article discusses on the proposed conceptual model for 3D realism towards meaning-making.It elaborates on principles of realism and 3D realism, meaning-making theories and processes and related works in the area.Based on four elements of 3D realism, it attempts to identify possible relationship with meaning making.The research methodology is outlined to achieve the intended research outcomes.The findings of this study would contribute to understanding of the ability to learning via 3D content

Assessing data analysis performance in research contexts: An experiment on accuracy, efficiency, productivity and researchers' satisfaction

[EN] Any knowledge generation process involves raw data comprehension, evaluation and inferential reasoning. These practices, common to different disciplines, are known as data analysis, and represent the most important set of activities in research contexts. Researchers use data analysis software methods and tools for generating new knowledge in their daily data analysis. In recent years, data analysis software has been incorporating explicit references in modelling of cognitive processes, in order to improve the assistance offered in data analysis tasks. However, data analysis software commercial suites are still resisting this inclusion, and there is little empirical work done in knowing more about how cognitive aspects inclusion in software helps researchers in analyzing data. In this paper, we evaluate the impact produced by the explicit inclusion of cognitive processes in the assistance logic of software tools design and development. We conducted an empirical experiment comparing data analysis performance using traditional software versus data analysis performance using software-assistance tools which incorporate cognitive processes in their design. The experiment is designed in terms of accuracy, efficiency, productivity and user satisfaction during the data analysis made by researchers. It allowed us to find some clear benefits of the cognitive inclusion in the software designed for research contexts, with statistically significant differences in terms of accuracy, productivity and researcher's satisfaction in support of this explicit inclusion, although some efficiency weaknesses are detected. We also discuss the implications of these results for the priority of cognitive inclusion in the software tools design for research contexts data analysis.This paper has the support of Generalitat Valenciana through project IDEO (PROMETEOII/2014/039) and Spanish Ministry of Science and Innovation through project DataME (ref: TIN2016-80811-P).Martín-Rodilla, P.; Panach Navarrete, JI.; González-Pérez, CA.; Pastor López, O. (2018). Assessing data analysis performance in research contexts: An experiment on accuracy, efficiency, productivity and researchers' satisfaction. Data & Knowledge Engineering. 116:177-204. https://doi.org/10.1016/j.datak.2018.06.003S17720411