A state of art survey on zz-structures

Zz-structures are particular data structures capable of representing both hypertextual information and contextual interconnections among different information. The focus of this paper is to stimulate new research on this topic, by providing, in a state of the art survey, a short description and comparison of all the material that, to the best of our knowledge, is related to zz-structures: informal and formal descriptions, implementations, languages, demonstrations, projects and applitudes of zz-structures; in fact, despite their large use in different fields, the literature lacks of an exhaustive and up-to-date description of them

User Interfaces for Personal Knowledge Management with Semantic Technologies

This thesis describes iMapping and QuiKey, two novel user interface concepts for dealing with structured information. iMapping is a visual knowledge mapping technique based on zooming, which combines the advantages of several existing approaches and scales up to very large maps. QuiKey is a text-based tool to interact with graph-structured knowledge bases with very high interaction efficiency. Both tools have been implemented and positively evaluated in user studies

Intertwingled: The Work and Influence of Ted Nelson

History of Computing; Computer Appl. in Arts and Humanities; Data Structures; User Interfaces and Human Computer Interactio

Mathematical surfaces models between art and reality

In this paper, I want to document the history of the mathematical surfaces models used for the didactics of pure and applied “High Mathematics” and as art pieces. These models were built between the second half of nineteenth century and the 1930s. I want here also to underline several important links that put in correspondence conception and construction of models with scholars, cultural institutes, specific views of research and didactical studies in mathematical sciences and with the world of the figurative arts furthermore. At the same time the singular beauty of form and colour which the models possessed, aroused the admiration of those entirely ignorant of their mathematical attraction

Generic adaptation framework for unifying adaptive web-based systems

The Generic Adaptation Framework (GAF) research project first and foremost creates a common formal framework for describing current and future adaptive hypermedia (AHS) and adaptive webbased systems in general. It provides a commonly agreed upon taxonomy and a reference model that encompasses the most general architectures of the present and future, including conventional AHS, and different types of personalization-enabling systems and applications such as recommender systems (RS) personalized web search, semantic web enabled applications used in personalized information delivery, adaptive e-Learning applications and many more. At the same time GAF is trying to bring together two (seemingly not intersecting) views on the adaptation: a classical pre-authored type, with conventional domain and overlay user models and data-driven adaptation which includes a set of data mining, machine learning and information retrieval tools. To bring these research fields together we conducted a number GAF compliance studies including RS, AHS, and other applications combining adaptation, recommendation and search. We also performed a number of real systems’ case-studies to prove the point and perform a detailed analysis and evaluation of the framework. Secondly it introduces a number of new ideas in the field of AH, such as the Generic Adaptation Process (GAP) which aligns with a layered (data-oriented) architecture and serves as a reference adaptation process. This also helps to understand the compliance features mentioned earlier. Besides that GAF deals with important and novel aspects of adaptation enabling and leveraging technologies such as provenance and versioning. The existence of such a reference basis should stimulate AHS research and enable researchers to demonstrate ideas for new adaptation methods much more quickly than if they had to start from scratch. GAF will thus help bootstrap any adaptive web-based system research, design, analysis and evaluation

Groups and communities at risk of domestic and family violence: a review and evaluation of domestic and family violence prevention and early intervention services focusing on at-risk groups and communities

A review and evaluation of domestic and family violence prevention and early intervention services focusing on at-risk groups and communities. Summary This report sets out the findings of research into domestic and family violence (DFV) prevention initiatives focused on groups and communities identified as being at greater risk of experiencing DFV and/or having difficulty accessing support services. These groups include Aboriginal and Torres Strait Islander women, women from Culturally and Linguistically Diverse Communities (CALD), people who identify as Gay, Lesbian, Bisexual, Transsexual, Intersex and Queer (GLBTIQ), young women and women in regional, rural and remote (non-urban) communitie

Lost in the archive: vision, artefact and loss in the evolution of hypertext

How does one write the history of a technical machine? Can we say that technical machines have their own genealogies, their own evolutionary dynamic? The technical artefact constitutes a series of objects, a lineage or a line. At a cursory level, we can see this in the fact that technical machines come in generations - they adapt and adopt characteristics over time, one suppressing the other as it becomes obsolete. It is argued that technics has its own evolutionary dynamic, and that this dynamic stems neither from biology nor from human societies. Yet 'it is impossible to deny the role of human thought in the creation of technical artefacts' (Guattari 1995, p. 37). Stones do not automatically rise up into a wall - humans 'invent' technical objects. This, then, raises the question of technical memory. Is it humans that remember previous generations of machines and transfer their characteristics to new machines? If so, how and where do they remember them? It is suggested that humans learn techniques from technical artefacts, and transfer these between machines. This theory of technical evolution is then used to understand the genealogy of hypertext. The historical differentiations of hypertext in different technical systems is traced. Hypertext is defined as both a technical artefact and also a set of techniques: both are a part of this third milieu, technics. The difference between technical artefact and technical vision is highlighted, and it is suggested that technique and vision change when they are externalised as material artefact. The primary technique traced is association, the organisational principle behind the hypertext systems explored in the manuscript. In conclusion, invention is shown to be an act of exhumation, the transfer and retroactiviation of techniques from the past. This thesis presents an argument for a new model of technical evolution, a model which claims that technics constitutes its own dynamic, and that this dynamic exceeds human evolution. It traces the genealogy of hypertext as a set of techniques and as series of material artefacts. To create this geneaology I draw on interviews conducted with Douglas Engelbart, Ted Nelson and Andries van Dam, as well as a wide variety of primary and secondary resources

Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018 : 10-12 December 2018, Torino

On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-­‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-­‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges