This paper describes the International Institute of Information Technology of Hyderabad’s submission to the task Classification Of Spanish Election Tweets (COSET) as a part of IBEREVAL-2017[1]. The task is to classify Spanish election tweets into political, policy, personal, campaign and other issues. Our system uses Support Vector Machines with radial basis function kernel to classify tweets. ...

We introduce a family of classifiers based on a physical analogy to an electrostatic system of charged conductors. The family, called Coulomb classifiers, includes the two best-known support-vector machines (SVMs), the ν–SVM and the C–SVM. In the electrostatics analogy, a training example corresponds to a charged conductor at a given location in space, the classification function corresponds to...

Decision support often focuses on substantive rationality (what to choose). The procedural rationality (how to choose) of the process of long-term strategic decision making is then often neglected. In strategic decision making, supporting the decision process is more important than supporting the search for an ‘‘optimal’’ solution to the problem, especially since for most policy problems a well...

This article describes an approach to bridging the gap between the generalist thinking of decision makers and the specialism of modellers by concentrating on the preliminary issue conceptualisation stage of modelling. A new type of visual facilitation is described using hexagons as a flexible mapping technique to bridge the gap between thoughts and models. A typical team application is describe...

In this paper we study the challenging problem of seafloor imagery taxonomic categorization. Our contribution is threefold. First, we demonstrate that this task can be elegantly translated into a Structured SVM learning framework. Second, we introduce a taxonomic loss function in the structured output classification objective during learning that is shown to improve the performance over other l...

The Support Vector Machines (SVM) is a classification algorithm with many diverse applications. The SVM has many parameters associated with it which influences the performance of the SVM classifier. In this paper, we employ Genetic Algorithm based approach to find and select an appropriate kernel function and its parameters. This proposed technique combines predictive accuracy and complexity of...

Disease diagnosis can be performed based on fusing the data acquired by multiple medical sensors from patients, and it is a crucial task in sensor-based e-healthcare systems. However, it is a challenging problem that there are few effective diagnosis methods based on sensor data fusion for atrial hypertrophy disease. In this article, we propose a novel multi-sensor data fusion method for atrial...

The paper is a comparative study of major modeling and pattern discovery approaches applicable to the area of Bioinformatics and the area of decision support systems in general. These approaches include inductive versus transductive reasoning, global, local, and personalized modeling and their potentials are illustrated on a case study of gene expression and clinical data related to cancer outc...

The purpose of this study is to examine the Twitter communica­ tion between school districts, superintendents, and the public. Content analysis of the tweets posted by the 100 largest U.S. school districts and those district superintendents was performed to investigate how the districts and the super­ intendents communicated with the public on Twitter. Next, paired sample f-tests were performed...

Due to the complexity of present day supply chains, it is important to select the simplest supply chain scheduling Decision Support System (DSS) which will determine and place orders satisfactorily. We propose to use a generic design framework, termed the explicit filter methodology, to achieve this objective. In doing so we compare the explicit filter approach to the implicit filter approach u...