Categorization of interestingness measures for knowledge extraction

Finding interesting association rules is an important and active research field in data mining. The algorithms of the Apriori family are based on two rule extraction measures, support and confidence. Although these two measures have the virtue of being algorithmically fast, they generate a prohibitive number of rules most of which are redundant and irrelevant. It is therefore necessary to use further measures which filter uninteresting rules. Many synthesis studies were then realized on the interestingness measures according to several points of view. Different reported studies have been carried out to identify "good" properties of rule extraction measures and these properties have been assessed on 61 measures. The purpose of this paper is twofold. First to extend the number of the measures and properties to be studied, in addition to the formalization of the properties proposed in the literature. Second, in the light of this formal study, to categorize the studied measures. This paper leads then to identify categories of measures in order to help the users to efficiently select an appropriate measure by choosing one or more measure(s) during the knowledge extraction process. The properties evaluation on the 61 measures has enabled us to identify 7 classes of measures, classes that we obtained using two different clustering techniques.Comment: 34 pages, 4 figure

Behavior change interventions: the potential of ontologies for advancing science and practice

A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using "ontologies." In information science, an ontology is a systematic method for articulating a "controlled vocabulary" of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science

Climate change and variability, energy and disaster management: produced risks without produced solutions: rethinking the approach

Accelerated climate change and increasing climate variability is the single largest threat to the international goals of sustainable development, the Millennium Development Goals (MDGs) and disaster risk reduction. Global discourses recognise the need for effective and sustainable responses tso produced climate risks. The risk types likely to occur are known, but only in broad terms - their scale, severity, longevity and frequency are not known. The challenge for policymakers is developing an effective framework within which sustainable responses can be formulated. To address the problems of produced risks a comprehensive approach to risk management is necessary. The mechanisms within the climate change, sustainable development and disaster risk reduction discourses are not sufficiently effective or integrated to respond to this challenge. Fundamental reform to current modes of risk reduction is needed, but this can only be achieved through a shift in the dominant perspective on formulating sustainable responses. This requires a shift to an enabling policy framework that encourages bottom-up resilient responses. Resilience is argued as a tool for policy development that can enhance adaptive capacity to current climate risks and shape energy policy to respond to mitigate future climate risks

International cooperation against climate change: institutions, policies and their efficiency

In the 20th century nature of the world economy has started to change significantly, and the former state-centric constellation disappeared. Several development factors that induced the change are still active and nowadays we live in a much different world. The world economy consists of transnational networks; these complicated systems have a great impact on the world of states. The transnational actors’ (multinational corporations, non-governmental organizations etc) influence became very essential as they are able to mobilize the society, have high expertise (think tanks), but it is also important to note their financial strength and moral effects (norm entrepreneurs)