The computational turn: thinking about the digital humanities

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Information in the Context of Philosophy and Cognitive Sciences

This textbook briefly maps as many as possible areas and contexts in which information plays an important role. It attempts an approach that also seeks to explore areas of research that are not commonly associated, such as informatics, information and library science, information physics, or information ethics. Given that the text is intended especially for students of the Master's Degree in Cognitive Studies, emphasis is placed on a humane, philosophical and interdisciplinary approach. It offers rather directions of thought, questions, and contexts than a complete theory developed into mathematical and technical details

Mining Threat Intelligence about Open-Source Projects and Libraries from Code Repository Issues and Bug Reports

Open-Source Projects and Libraries are being used in software development while also bearing multiple security vulnerabilities. This use of third party ecosystem creates a new kind of attack surface for a product in development. An intelligent attacker can attack a product by exploiting one of the vulnerabilities present in linked projects and libraries. In this paper, we mine threat intelligence about open source projects and libraries from bugs and issues reported on public code repositories. We also track library and project dependencies for installed software on a client machine. We represent and store this threat intelligence, along with the software dependencies in a security knowledge graph. Security analysts and developers can then query and receive alerts from the knowledge graph if any threat intelligence is found about linked libraries and projects, utilized in their products

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results

Working out a common task: design and evaluation of user-intelligent system collaboration

This paper describes the design and user evaluation of an intelligent user interface intended to mediate between users and an Adaptive Information Extraction (AIE) system. The design goal was to support a synergistic and cooperative work. Laboratory tests showed the approach was efficient and effective; focus groups were run to assess its ease of use. Logs, user satisfaction questionnaires, and interviews were exploited to investigate the interaction experience. We found that user’ attitude is mainly hierarchical with the user wishing to control and check the system’s initiatives. However when confidence in the system capabilities rises, a more cooperative interaction is adopted

SDRS: a new lossless dimensionality reduction for text corpora

In recent years, most content-based spam filters have been implemented using Machine Learning (ML) approaches by means of token-based representations of textual contents. After introducing multiple performance enhancements, the impact has been virtually irrelevant. Recent studies have introduced synset-based content representations as a reliable way to improve classification, as well as different forms to take advantage of semantic information to address problems, such as dimensionality reduction. These preliminary solutions present some limitations and enforce simplifications that must be gradually redefined in order to obtain significant improvements in spam content filtering. This study addresses the problem of feature reduction by introducing a new semantic-based proposal (SDRS) that avoids losing knowledge (lossless). Synset-features can be semantically grouped by taking advantage of taxonomic relations (mainly hypernyms) provided by BabelNet ontological dictionary (e.g. “Viagra” and “Cialis” can be summarized into the single features “anti-impotence drug”, “drug” or “chemical substance” depending on the generalization of 1, 2 or 3 levels). In order to decide how many levels should be used to generalize each synset of a dataset, our proposal takes advantage of Multi-Objective Evolutionary Algorithms (MOEA) and particularly, of the Non-dominated Sorting Genetic Algorithm (NSGA-II). We have compared the performance achieved by a Naïve Bayes classifier, using both token-based and synset-based dataset representations, with and without executing dimensional reductions. As a result, our lossless semantic reduction strategy was able to find optimal semantic-based feature grouping strategies for the input texts, leading to a better performance of Naïve Bayes classifiers.info:eu-repo/semantics/acceptedVersio

Changing narratives: colonised peoples, criminology and social work

Abstract: There is growing recognition in criminology and social work of the importance of Indigenous knowledges and methodologies. Yet to date there have been limited attempts (particularly in criminology and criminal justice social work) to consider the theoretical and practice implications of Indigenous understandings and approaches to these disciplines. Both disciplines have also been slow to recognise the importance of understanding the way in which colonial effects are perpetuated through knowledge control, particularly in the operation of criminal justice systems. Our paper thus begins by examining the historical and institutional factors that have contributed to the continuing subjugation of Indigenous knowledges and methodologies. A discussion of the connections between the hegemony of Western science, the construction of race, and the colonial project follows. While herein Western and Indigenous approaches are conceptualised broadly, the dangers of over-simplifying these categories is also acknowledged. The paper proceeds by examining the distinctive character of each approach through a consideration of their ontological, epistemological, axiological, and methodological differences. Whilst acknowledging the considerable challenges which arise in any attempt to develop connections between these differing worldviews, a pathway forward for understanding both theoretically and methodologically the relationship between Western and Indigenous approaches is proposed