Research on marketing and deception has identified principles of persuasion that influence human decisions. However, this research is scattered: it focuses on specific contexts and produces different taxonomies. In regard to frauds and scams, three taxonomies are often referred in the literature: Cialdini’s principles of influence, Gragg’s psychological triggers, and Stajano et al. principles o...

Will Advanced Driving Assistance Systems (ADAS) and Highly Automated (HAD) perform in the expected manner? they actually make road traffic safer, or will potentially introduce new critical situations accidents? It is almost impossible to address these questions solely through real-world tests. A promising tool provide appropriate answers a time-and cost-efficient way without exposing subjects r...

Hierarchies are an intuitive and effective organization paradigm for data. Of late there has been considerable research on automatically learning a hierarchical organizations of data. In this paper, we formulate the problem of “automatically constructing hierarchical taxonomies”, which we define as learning a hierarchy of categories with no user defined parameters. We propose a framework that c...

Biomedical ontologies are generally very large and complex. Their size and complexity make quality assurance a difficult and timeconsuming task. Compact networks called abstraction networks can be derived to summarize the content and structure of ontologies and support their quality assurance. The Biomedical Layout Utility for SNOMED CT (BLUSNO) is a system for automatically deriving and visual...

Classification schemes such as taxonomies are important groundwork for research on many topics in Information Systems (IS) and Management. They make investigating topics manageable by allowing researchers to delimit their work to certain taxa or types and provide a basis for generalization. Opposed to theoretically grounded typologies, taxonomies are empirically derived from entities of a pheno...

Knowledge representations using semantic web technologies often provide information which translates to explicit term and predicate taxonomies in relational learning. We show how to speed up the propositionalization by orders of magnitude, by exploiting such taxonomies through a novel refinement operator used in the construction of conjunctive relational features. Moreover, we accelerate the su...

Recent work in automatic question answering has called for question taxonomies as a critical component of the process of machine understanding of questions. There is a long tradition of classifying questions in library reference services, and digital reference services have a strong need for automation to support scalability. Digital reference and question answering systems have the potential t...